This data science LinkedIn profile guide will help you create an optimised, appealing profile that headhunters and recruiters on the hunt for your expertise will love. Not only do you see posts from connections in your network, but also activity from groups and communities you join or follow. So what does this mean for you as someone in data science, engineering, or machine learning? You should use this section to feature the highlights that would be included in your CV and are of interest to potential employers. Adel has 6 jobs listed on their profile. A. – Make use of data science LinkedIn groups. Detailing your past and present roles provide recruiters with the most detailed insight. A report by Ryan Swanstrom demonstrates the comparison of skills included on LinkedIn profiles for data scientists, software engineers, and data engineers. In 2010, former Google CEO Eric Schmidt famously said that every two days we create as much data as we did from the dawn of time through 2003. You can be certain that you’re not going to hear from many headhunters if you do not have this enabled. It will increase your chances of being a successful candidate when applying for roles – and that’s the end goal, right? The social networking platform bridges the gap between candidates and clients, which has led to more than 75% of professionals now using LinkedIn. I’d rather see a profile description that has a concise overview of key work objectives and experience. – Tom Harris – Principal Consultant (Data Science, Machine Learning, Deep Learning, Computer Vision & Artificial Intelligence). Buzzword Bingo. Can you crawl data from LinkedIn? In fact, according to a report by O’Reilly Media, nearly half of all European companies are struggling to fill data science positions. Take the time to check you have your settings optimised so that you can be contacted by a recruiter. Now, this section is where you’re going to get the bulk of your information laid out in your profile. If you’ve already published articles related to Machine Learning, Deep Learning, Artificial Intelligence & Data Science, repurpose these and upload them to your LinkedIn profile to support the growth of your network. There will be those that share similar experience and skills as you, so you’ll want to make a conscious effort to keep your profile clear and concise. . . Nobody wants to read through war and peace when visiting a LinkedIn profile. Terms of Service. Now the key here is to think about how many times have you worked on something that falls outside of your Data Scientist role. For example, visitors of your page can see whom you are connected with, which topics you’re discussing, and the industries that you’re tapped into. Q. Archives: 2008-2014 | Yet the more information you are able to provide could benefit you in the long run. So I sought data on who is. You might also be wondering why you’re not seeing the results you had hoped for if you’re already using LinkedIn to apply for vacancies. You’re helping them delve deeper into why you are a perfect fit for an exciting new job role. When it comes to working within data science, most organisations are looking for candidates with a core set of industry-standard skills. The social networking platform bridges the gap between candidates and clients, which has led to more than 75% of professionals now using LinkedIn. We’d suggest making a start here. Be straight to the point and avoid confusing individual areas of your expertise when you list them. Of course, it might not always be appropriate for you to disclose every little detail about your role depending on your profession. Is Your Machine Learning Model Likely to Fail? This is where interests come in. Lead the Data Science Team with the challenging responsibility to grow the area by designing new product offers and prepare a team to be technically able to deliver all of this. There are too many candidates out there applying for jobs that fail to either possess or include key skills such as Python, Data Science, Machine Learning & AWS. Not only do you see posts from connections in your network, but also activity from groups and communities you join or follow. Most certainly yes. Emily Natasha Díaz - Specialist, Data Science - QuantumBlack | … Taken from a headhunters perspective, we take a look at what information is the most appealing when a job application is being reviewed. Now that we know what Alyesha does and the industry she is working in, we’re more likely to want to explore the rest of her profile to develop further understanding of her past and present professional roles. There are plenty of resources available online which can teach you how to take professional photos using your phone in no time at all such as this step by step tutorial. Taken from a headhunters perspective, we take a look at what information is the most appealing when a job application is being reviewed. The more information available from an applicant, the better. About. Here’s an example from an Associate Director of Data Science: Your profile immediately becomes more attractive to recruiters when they’re able to get a clear insight into everything that you’ve worked on. When it comes to showcasing your strengths, the skills and endorsements section on your LinkedIn profile is of great value. A. By default, your 4 most recent interactions with other users across the whole of LinkedIn will be displayed in your activity feed within your profile. Not including any images in your profile gives the impression that you are not active on the platform. Gone are the days of scouring the loft of your parents house to hunt for the family polaroid to get the perfect headshot. Leading the data science group at appsflyer. This is a lot of information to convey to somebody who doesn’t already know Alyesha, however when visiting her LinkedIn profile, we’re able to identify exactly what Alyesha does due to her profile being optimised effectively to communicate her job role and the company she works for. This leaves a lot of guesswork for a recruiter to identify where your strengths and expertise are. The benefits of keeping your LinkedIn profile up to date are pretty obvious. Also, it’s never nice to read somebody talking about themselves in the third person – Dan Kettle – Senior Technical Recruiter (Data Science, Machine Learning & Artificial Intelligence). You have the ability to list each individual role that you’ve worked in. Use LinkedIn to be helpful, conversational and offer your opinion. It’s imperative you optimise your skillsets on LinkedIn, and you should start now! This activity is visible to anybody who visits your page and it is worth keeping this in mind when you are communicating with other LinkedIn users and organisations. Be straight to the point and avoid confusing individual areas of your expertise when you list them, It’s worth considering that in your busy schedule, you might have overlooked certain aspects of your work. You could share mutual interests when it comes to the daily documentation of Elon Musks ambitious statements for example. I’d rather see a profile description that has a concise overview of key work objectives and experience, . Strive to have your capabilities, personality and work ethic credited through personal recommendations. This demonstrates the completion of projects performed, further supporting the role. Remember that LinkedIn is saturated with data science professionals. If you’ve already published articles related to Machine Learning, Deep Learning, Artificial Intelligence & Data Science, repurpose these and upload them to your LinkedIn profile to support the growth of your network. This is an immediate deterrent for recruitment and HR professionals. We can guarantee it. (document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq); })(); By subscribing you accept KDnuggets Privacy Policy, Despite this number of Data Scientists available/in roles online currently, it’s no secret there is still a major talent shortage, half of all European companies are struggling to fill data science positions, Studies performed by Indeed’s Hiring Lab show an, increase of 256% in data science job openings since 2013, with an increase of 31% year over year from as recent as December 2018. . Your profile header is the first thing visitors to your page are going to see. . Showing your audience who are you with the perfect headshot is the first step to introducing yourself in a more personable manner, encouraging others to get to know you. Welcome to our data science experience, this month Matteo Landrò, Data Scientist at SAS introduces his views on Model Management. Some people might be asking a question that you have the answer to. You could share mutual interests when it comes to the daily documentation of Elon Musks ambitious statements for example, we’ve covered the areas in which you can make the most out of your LinkedIn profile, let’s drill down into the data science recruitment process, hold more than 20+ years of experience in the talent search. Detailing your past and present roles provide recruiters with the most detailed insight. It represents us directly.’, This data science LinkedIn profile guide will help you create an optimised, appealing profile that headhunters and recruiters on the hunt for your expertise will love, Whichever category you fit into, you should consider using your profile as the ideal platform to document your role responsibilities, projects, and activities you’ve completed. Take the time to check you have your settings optimised so that you can, within the first 5 – 10 seconds of browsing an applicants profile. Q. So what does this look like on your profile? . This will inform their decision when making a change in their careers. This provides the opportunity to explain your role, skills and experience in more detail. Kimberly Hermans | Antwerp Area, Belgium | Data Science Manager at Ordina Belgium | 500+ connections | See Kimberly's complete profile on Linkedin and connect You’re a hot commodity. Better still, support your skillset within the context of a project description. within the role description. This may harm how are you perceived if scouted by recruiters for new career opportunities. He devotes his time with Data Science Nigeria, the leading AI Company in Nigeria as a Research and Innovation Intern on projects and researchs. , we can see that this individual works at Big Cloud as a Social Media Manager. Top 10 LinkedIn Groups for Data Science Professionals | by Digital … It’s important not to miss the opportunity here to go into more detail about your role and responsibilities. Your LinkedIn news feed tailors to you. It doesn’t have to be professional! With over 575 million registered users and more than 260 million of those active on a monthly basis, LinkedIn is, You have the opportunity to connect with influencers, decision-makers and leaders within your industry, The social networking platform bridges the gap between candidates and clients, which has led to more than 75% of professionals now using LinkedIn. It doesn’t belong to our core responsibilities, but these moments provide the ideal opportunity to showcase your ability to go the extra mile and work as part of a team to support the business, Your profile immediately becomes more attractive to recruiters when they’re able to get a clear insight into everything that you’ve worked on. A comparison of skills listed on LinkedIn by Data Scientists, Software Engineers & Data Engineers. Of course, it might not always be appropriate for you to disclose every little detail about your role, depending on your profession. 2015-2016 | There are plenty of resources available online, which can teach you how to take professional photos using your phone in no time at all such as this step by step tutorial. We offer an open community platform to connect, educate and empower students will the skills to unlock the power of data science. If there’s no evidence that you have applied your experience to any given project, it implies you’re not qualified for the role you’re applying for, how many applications I receive from Data Scientists that do not include any references to projects that they have worked on. show you have experience in. This demonstrates the completion of projects performed, further supporting the role. Data Science LinkedIn Experience and Work History. O’Donnell (founder and CEO of Work It Daily) puts it, ‘a LinkedIn profile is ‘ours to manage. Better still, support your skillset within the context of a project description. Our data scientists dig gold from the ground for our customers, delivering intelligent products over that huge amount of data. Did you know that your LinkedIn profile displays your recent activity across the entire platform? You can be certain that you’re not going to hear from many headhunters if you do not have this enabled. injected some personality into their profile. They are only visible on your profile once you have approved them. A. This provides the opportunity to explain your role, skills, and experience in more detail. Better still, support your skillset within the context of a project description. – Nicholas Jackson – Data Science Recruiter (Machine Learning, Deep L... Q. This is where interests come in. Here’s an example from an Associate Director of Data Science: Your profile immediately becomes more attractive to recruiters when they’re able to get a clear insight into everything that you’ve worked on. LinkedIn is the premier place for professionals to gather, connect with one another, share ideas, and network. When posting content or comments that demonstrate your opinion on a particular topic, it is considered best practice to refrain from engaging in negative activity. Despite this number of Data Scientists available/in roles online currently, it’s no secret there is still a major talent shortage. Curious about Data-driven science, where actions are based on trends. Let’s say you’ve described yourself as a team player in your profile description. Don’t worry though, we’ve made this part easy by creating the only CV template you’ll ever need which you can download for free below. This near enough always encourages me to keep reading through their information. Expand upon your experience and career development to set yourself apart from the competition. Joining groups is a great way to meet new people who share common interests with you. I think it would be hugely beneficial for data science applicants to make use of LinkedIn’s article writing as it’s great for raising awareness of who you are and gives recruiters more insight into your experience when browsing your profile. This data science LinkedIn profile guide will help you create an optimised, appealing profile that headhunters and recruiters on the hunt for your expertise will love. Strive to have your capabilities, personality, and work ethic credited through personal recommendations. lots of text in your profile summary is off-putting and unnecessary. It represents us directly.’. lots of text in your profile summary is off-putting and unnecessary. It means I can direct them to more relevant and exciting roles and nobodies time, A. You’ve made it this far in setting up your page, but it begs the question, how else can you make use of LinkedIn? Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. For example; If you’re a data science professional, your skills might include some of the following: Word of mouth still is and always will be one of the most important forms of referral. This will further outline your professional portfolio and capabilities. In addition to showcasing your best smile, you’ll also want to make sure that you have a header image which preferably relates to your area of expertise. Of course, it might not always be appropriate for you to disclose every little detail about your role, depending on your profession. Remember to keep it professional and refrain from sharing negative views, which could harm your chances of being approached by a new employer. the skills and endorsements section on your LinkedIn profile is of great value. Keep all of your writing as human as possible. What are the most common mistakes you see on a data scientist profile? Data science is a vast, complex industry with many subsets. Tom Harris – Principal Consultant (Data Science, Machine Learning, Deep Learning, Computer Vision & Artificial Intelligence), Nicholas Jackson – Data Science Recruiter (Machine Learning, Deep Learning, Computer Vision & Artificial Intelligence), Chris Bradbury – (Deep Learning & Computer Vision Recruiter), Carsten Jahn – Recruiting AI Experts (ML/DL, CV, NLP & Robo). It’s also a huge bonus if the candidate has listed examples of projects that they have worked on. It will increase your chances of being a successful candidate when applying for roles – and that’s the end goal, right? Some tasks or projects might not fit your job description on paper, but if they support areas of your expertise that an employer will look for, use them! By Dan Lewins, Social Media Manager at Big Cloud. Not only that, but you’ll also be upload your your cv directly to a new opportunity. For me, I just need 3 – 4 sentences on each role that a candidate has held with a clear list of the tech they’ve worked on, whether that be in the profile summary or listed in keywords. This will inform their decision when making a change in their careers. If you have these included in your profile, it makes a big difference. One thing that always stands out to me is when a candidate has included a link to either their own website or Github profile. var disqus_shortname = 'kdnuggets'; Highly creative, self-motivated, committed to staying current on innovation in technology, computer science, data science and engineering. Your profile header is the first thing visitors to your page are going to see. Ideal candidates that Alyesha will be looking to work with will hold specialist skills in Language Technologies, Explainable AI and People Analytics. AppsFlyer is the world largest mobile attribution platform, as such the company manages enormous amounts of data. Despite this number of Data Scientists available/in roles online currently, it’s no secret there is still a major talent shortage. – Include extracurricular activities, volunteer experience, and additional spoken/written languages. – Devise and utilise algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy. Data science is a vast, complex industry with many subsets. Driving business decisions using data science and machine … Including recommendations by people you’ve worked with before gives employers live references. . Strive to have your capabilities, personality and work ethic credited through personal recommendations. What would you recommend to a data science LinkedIn candidate who wanted to stand out when applying for a job? This leaves a lot of guesswork for a recruiter to identify where your strengths and expertise are. Download all photos and use them even for commercial projects. Deploying Trained Models to Production with TensorFlow Serving, A Friendly Introduction to Graph Neural Networks. Please check your browser settings or contact your system administrator. The ‘about’ section immediately follows your header. If there is no information listed under each role, I’ll most likely move onto the next applicant – Chris Harrison – Senior Consultant (Data Science, Machine Learning, Artificial Intelligence, Deep Learning, NLP & Big Data), The more information is available from an applicant, the better. Including recommendations by people you’ve worked with before gives employers live references. Joining groups is a great way to meet new people who share common interests with you. Towards Data Science - Mining Data on LinkedIn. Is it just us, or do you hear crickets chirping while waiting for something to happen? We’ve all worked on a task or project at one point to support a colleague or a separate department. I also work closely with the engineering team to strategise and execute the development of data products. Top 13 Skills To Become a Rockstar Data Scientist, Projects to Include in a Data Science Portfolio, SQream Announces Massive Data Revolution Video Challenge. When it comes to working within data science, most organisations are looking for candidates with a core set of industry-standard skills. One thing that always stands out to me is when a candidate has included a link to either their own website or Github profile. Q. Don’t be shy in communities, use them as an opportunity to network and learn something new. For recruitment specialists, they want to be able to identify candidates who can offer organisations a unique set of skills. Your LinkedIn news feed tailors to you. If you’re open to new opportunities but aren’t accepting InMails, you could be missing out on new, exciting roles. It’s also worth noting that your interests are visible to your profile visitors. Example 1: Here we can see that this individual is working at Big Cloud as a Social Media Manager. With so many Data Scientists showing up on LinkedIn, it's time to make sure your profile is top-notch because your talent is still highly sought after. They have a break down of what the role entails exactly. Some people might be asking a question that you have the answer to. Data Science Connect | 969 followers on LinkedIn. The way we see it, the more effort you put into your profile, the more opportunity you will see from it. Write in first person, not in third. If there’s no evidence that you have applied your experience to any given project, it implies you’re not qualified for the role you’re applying for. Using groups will allow you to join communities and make connections with others who relate to your areas of interest. Q. Only list skills that you can clearly show you have experience in. A good or bad bio could mean the difference between receiving valuable opportunities or losing them. It’s refreshing when candidates have distinctlyinjected some personality into their profile. It will give you a place of reference to always look back and reflect on. Top Stories, Nov 16-22: How to Get Into Data Science Without a... 15 Exciting AI Project Ideas for Beginners, Know-How to Learn Machine Learning Algorithms Effectively, Get KDnuggets, a leading newsletter on AI, This offers an extra opportunity for your audience to get to know a bit more about you. A strong candidate will have taken time to perfect their profile and communicate their professional experience. This means you could be a great candidate but might not be contacted because your profile doesn’t reflect who you are and what you can do. Leiden Centre of Data Science | 266 volgers op LinkedIn. Studies performed by Indeed’s Hiring Lab show an overall increase of 256% in data science job openings since 2013, with an increase of 31% year over year from as recent as December 2018. Whilst you’re filling out this section of your profile, it would make good sense to update your CV at the same time. Specifically, professionals working within Data Science, Machine Learning & Artificial Intelligence organisations. Also, it’s never nice to read somebody talking about themselves in the third person – Dan Kettle – Senior Technical Recruiter (Data Science, Machine Learning & Artificial Intelligence). Not including any images in your profile gives the impression that you are not active on the platform. Did you know that your LinkedIn profile displays your recent activity across the entire platform? Now, this section is where you’re going to get the bulk of your information laid out in your profile. Yet the more information you are able to provide could benefit you in the long run. Here, you can highlight your specialisms with reaffirmation from your peers. You’d be surprised how many applications I receive from Data Scientists that do not include any references to projects that they have worked on – Alyesha Sayle – Senior Technical Recruiter (Language Technologies, Explainable AI & People Analytics). While it’s good to have many recommendations on your profile, we’d suggest only approving those that feature your skills. It doesn’t have to be professional! Let’s look at a couple of examples here to give this more context: Here, we’ll use the example of Big Cloud recruitment’s Social Media Manager. Are there any specific skills that you look for that makes a candidate more likely to be successful? Here’s how your contact settings should look: Allowing recruiters to contact you by InMail is vital if you’re hoping to receive new vacancy information. I wasn’t getting hired as a Data Scientist. It doesn’t belong to our core responsibilities, but these moments provide the ideal opportunity to showcase your ability to go the extra mile and work as part of a team to support the business. , all whilst ensuring you’re selling yourself to the best of your ability. Hadrien Lacroix | Paris, Île-de-France, France | Data Science Curriculum Manager at DataCamp | 500+ relations | Voir le profil complet de Hadrien sur LinkedIn et se connecter For the majority of employers, being able to work as part of a team is a mandatory, Using LinkedIn to document the finer details of your day to day duties gives you the chance to prove that you are in fact very capable of working within a team, – As a lead data strategist, I identify and integrate new datasets that can, with the engineering team to strategise and execute the development of data products, – Execute analytical experiments to help solve various problems, making a true impact across various domains and industries, – Identify relevant data sources and sets to mine for client business needs and collect large structured/unstructured datasets and variables, – Devise and utilise algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and, – Analyse data for trends and patterns and interpret data with a clear, analytical models into production by collaborating with software developers and machine learning engineers, – Communicate analytic solutions to stakeholders and, improvements as needed to operational systems, Now the key here is to think about how many times have you worked on something that falls outside of your Data Scientist role. This can become a great resource at a later stage in your career as you’ll have a record of your personal progression. . It is no different than Twitter, Instagram or Facebook. Studies performed by Indeed’s Hiring Lab show an overall increase of 256% in data science job openings since 2013, with an increase of 31% year over year from as recent as December 2018. You might also be wondering why you’re not seeing the results you had hoped for if you’re already using LinkedIn to apply for vacancies. we can see that this individual works at Big Cloud as a Social Media Manager. Here’s how your recommendations will appear on your profile: Written recommendations will only come from individuals you’re connected with. Your aim is to convey not only your strengths and abilities but also who you are as an individual. Joining groups is a great way to meet new people who share common interests with you. This is an immediate deterrent for recruitment and HR professionals. Make the most out of these features to assist in making your profile visually arresting. There are too many candidates out there applying for jobs that fail to either possess or include key skills such as Python, Data Science, Machine Learning, and AWS. populated with professionals working within the same space, you need to focus on making yourself outshine the competition, “Big Data is like teenage sex: everyone talks about it, nobody, knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it, As LinkedIn continues to expand its rate of active users, it’s more important than ever to ensure you’re making the most out of the platform. Most certainly yes. – Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems. Being able to dive right into an applicants background and ability always stands out to me when I’m reviewing applications and I’ll be more inclined to contact candidates who have considered including this information – Jess Bergin – Senior Technical Candidate Recruiter (Machine Learning, NLP & Conversational AI). They will list the company they work for and the date range in which they’re employed at that company. Q. Be straight to the point and avoid confusing individual areas of your expertise when you list them. Report an Issue  |  . Whichever category you fit into, you should consider using your profile as the ideal platform to document your role responsibilities, projects and activities you’ve completed. They will list the company they work for and the date range in which they’re employed at that company. As J.T. This will further outline your professional portfolio and capabilities. In addition to strategic and leadership based responsibilities, my day to day work involved performing analytics / machine learning to inform urban challenges, geospatial data science and teaching data visualisation methods to SMEs. Why? Q. Specifically, professionals working within Data Science, Machine Learning & Artificial Intelligence organisations. For me, I just need 3 – 4 sentences on each role that a candidate has held with a clear list of the tech they’ve worked on, whether that be in the profile summary or listed in keywords. Are publications written by Data Scientists on LinkedIn important to you when you’re reviewing a job application? It’s refreshing when candidates have distinctly. When it comes to showcasing your strengths, the skills and endorsements section on your LinkedIn profile is of great value. So what does this mean for you as someone in data science, engineering or machine learning? Let’s get this out of the way right off the bat, because many of you are likely skeptical of data science already for many of the reasons we were. Big Data and Data Science Hype. By now, you should have a good idea of what happened to the many job applications you made before you updated your LinkedIn profile. For recruitment specialists, they want to be able to identify candidates who can offer organisations a unique set of skills. . There are start-ups, unicorns, and conglomerates that will want to work with you. Tom Harris – Principal Consultant (Data Science, Machine Learning, ... Nicholas Jackson – Data Science Recruiter (Machine Learning, Deep L... 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Use every line within your profile description to sell what it is that you do and what you can offer. It is no different from Twitter, Instagram, or Facebook. The less information you have available on your profile, the lower the chances of your account showing as fitting for a potential new role. Showcase your expertise by writing articles surrounding your specialist subject, reactions to industry trends, and events in support of generating a following amongst your industry. When it comes to showcasing your strengths, the skills and endorsements section on your LinkedIn profile is of great value. It’s refreshing when candidates have distinctly injected some personality into their profile. By now you should have a good idea of what happened to the many job applications you made before you updated your LinkedIn profile. Solutions Review’s editors have compiled this directory of the top data science LinkedIn groups for practitioners. Consider the ‘about’ section as nothing more than a summary. Better yet, include both if you have both. While you’re filling out this section of your profile, it would make good sense to update your CV at the same time. You’re helping them delve deeper into why you are a perfect fit for an exciting new job role. This demonstrates the completion of projects performed, further supporting the role. Each entry within your experience section enables you to provide links to websites and the ability to upload images to enhance the view of your entries. This is how your recent activity is presented on your profile: Giving your audience insight into what you’re doing on LinkedIn showcases a number of things. With over 575 million registered users and more than 260 million of those active on a monthly basis, LinkedIn is undoubtedly the #1 professional networking platform. Having an up to date CV will increase your appeal when you apply for jobs using LinkedIn’s EasyApply feature. About. This is a lot of information to convey to somebody who doesn’t already know Alyesha, however when visiting her LinkedIn profile, we’re able to identify exactly what Alyesha does due to her profile being optimised effectively to communicate her job role and the company she works for. Privacy Policy  |  Buzzword Bingo. You have the opportunity to connect with influencers, decision-makers, and leaders within your industry. Additional contributions are documented within the role description. Being able to dive right into an applicants background and ability always stands out to me when I’m reviewing applications, and I’ll be more inclined to contact candidates who have considered including this information – Jess Bergin – Senior Technical Candidate Recruiter (Machine Learning, NLP & Conversational AI). – Implement analytical models into production by collaborating with software developers and machine learning engineers. Recruiters often comment on the lack of professionalism that comes across from writing about yourself in the third person. We’ve all worked on a task or project at one point to support a colleague or separate department. Remember, following your picture, this is the first part of your profile employers will see, so it’s important you get it right. You have the ability to list each individual role that you’ve worked in. Here, you can highlight your specialisms with reaffirmation from your peers. | by Jonas Schröder | Towards … It’s also worth noting that your interests are visible to your profile visitors. Your standard role requirements may look something like this: – As a lead data strategist, I identify and integrate new datasets that can be leveraged through our product capabilities. ONUIGWE VITUS is an AI Researcher, a Mentor, an Ambassador at deeplearning.ai, and the Team Lead Pie & AI Abuja. Not only do you see posts from connections in your network, but also activity from groups and communities you join or follow, . Not including any images in your profile gives the impression that you are not active on the platform, . Remembering Pluribus: The Techniques that Facebook Used... 14 Data Science projects to improve your skills. Keep your descriptions short and to the point, avoiding lengthy sentences and paragraphs. Consider the ‘about’ section as nothing more than a summary. You might be wondering,  however why you would need to keep on top of this if you’re not actively seeking out new opportunities. To date, there are more than 830,000 data science LinkedIn profiles registered worldwide. Take the time to check you have your settings optimised so that you can be contacted by a recruiter. To not miss this type of content in the future, subscribe to our newsletter. It’s worth considering that in your busy schedule, you might have overlooked certain aspects of your work. This can become a great resource at a later stage in your career as you’ll have a record of your personal progression. What would you recommend to a data science LinkedIn candidate who wanted to stand out when applying for a job? We are transforming how the world interacts with data through innovative and nontraditional content - datasciconnect.com | … The Big Cloud recruitment team collectively holds more than 20+ years of experience in the talent search. It’s also a huge bonus if the candidate has listed examples of projects that they have worked on. – Carsten Jahn – Recruiting AI Experts (ML/DL, CV, NLP & Robo). UNSW Data Science Society | 349 followers on LinkedIn | The first undergraduate Data Science Society in Australia | Hello and welcome! Feel ready to apply for your next data science, machine learning & artificial intelligence role? This makes you more likely to become headhunted by organisations who are in need of candidates with your expertise! You’re helping them delve deeper into why you are a perfect fit for an exciting new job role. This will increase your likelihood of being contacted, all while ensuring you’re selling yourself to the best of your ability. A report by Ryan Swanstrom demonstrates the comparison of skills included on LinkedIn profiles for data scientists, software engineers and data engineers. It’s important not to miss the opportunity here to go into more detail about your role and responsibilities. Variations in roles oftentimes require such specific skillsets that positions are left unfilled for an average of up to 45 days. Treat this section as an opportunity to document your work within each role well. . Yet the more information you can provide could benefit you in the long run. In addition to showcasing your best smile, you’ll also want to make sure that you have a header image that preferably relates to your area of expertise. You should use this section to feature the highlights that would be included in your CV and are of interest to potential employers. Facebook, Added by Tim Matteson It doesn’t belong to our core responsibilities, but these moments provide the ideal opportunity to showcase your ability to go the extra mile and work as part of a team to support the business. You could share mutual interests when it comes to the daily documentation of Elon Musks' ambitious statements for example. This will increase your likelihood of being contacted, all whilst ensuring you’re selling yourself to the best of your ability. It’s also a huge bonus if the candidate has listed examples of projects that they have worked on. Recruiters will use recommendations to verify your ability to perform within a given role. Now that you’ve given your profile a whole new lick of paint, let’s check some basic settings. Of course, there’s always going to be a crossover of skills between certain roles within our industry, however if your skills are clearly listed within each relevant role with details of how they were implemented, it becomes clearer to the recruiter reviewing your profile where they have previously been applied. I think it would be hugely beneficial for data science applicants to make use of LinkedIn’s article writing as it’s great for raising awareness of who you are and gives recruiters more insight into your experience when browsing your profile. If you’re open to new opportunities but aren’t accepting InMails, you could be missing out on new, exciting roles. If you don’t let recruiters know that you’re looking for new opportunities, you’re not going to hear from. Use LinkedIn to be helpful, conversational, and offer your opinion. Find the best free stock images about data science. If you have these included in your profile, it makes a big difference. To make sure that you can be contacted by recruiters, you’re going to need to make sure that you have enabled specific settings on your profile. This can become a great resource at a later stage in your career as you’ll have a record of your personal progression. Nobody wants to read through war and peace when visiting a LinkedIn profile. . sat down with the recruitment team to gain more insight into how you can avoid common mistakes frequented on data science profiles. Treat this section as an opportunity to document your work within each role well. Additional contributions are documented within the role description. This makes you more likely to become headhunted by organisations who are in need of candidates with your expertise! The less information you have available on your profile, the lower the chances of your account showing as fitting for a potential new role. Your colleagues and superiors for the majority of employers, being able to provide could benefit you in the run! 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