Hari Prasad Renganathan’s Post

Data science is a burgeoning field but are you aware if it's the best career option for you? Before taking the plunge, it's essential to evaluate if it's the best option for you. Our latest article delves deep into the data science job market, exploring job roles, required skills, salaries, and challenges. Gain insights to help you make an informed decision about pursuing a career in data science. The link is here: https://loom.ly/vQyBX5M

Data Science Creators are wrong. You need to stop building a portfolio: You likely already have the skills you need. But you need to communicate your value. I learnt this the hard way when I thought I'd smashed an interview. Only to get devastating feedback saying they'd barely understood what I talked about. This catalysed me to get my shit together, and after my next interview I was offered a Data Scientist job in the Government Department for Energy. So stop building projects. And start talking sense.

😫 Navigating the Data Science job market can be a daunting task, especially when it comes to deciphering job titles. The wide range of skills from AB Testing to AI, makes it a role with a wide spectrum of roles, all masked as ‘Data Scientist’. In reality, some teams emphasize specific skills over others, while others require Data Scientists to be versatile full-stack engineers capable of writing and productionizing code end-to-end. Adding to the complexity, some Data Science teams operate centrally across various product areas, while others are embedded within specific product areas. This diversity can lead to confusion among candidates. They often apply for roles across different specializations, hoping to find the perfect fit for their skills and passions. 🙋 Join me for a free webinar where we'll delve into strategies for unlocking Data Science opportunities. We will deep dive into: - Breaking down data science roles - Reading through job descriptions carefully to understand the type of data science role - assessing your skills, and finding a position that aligns with your skills and passions - Tips to unlock more opportunities to advance your career Join live on April 26. Register here: https://bit.ly/3xxorhV

My observation from job market. There are much fewer jobs for data scientists/analysts compared to web-devs. And it's natural: not many companies have big data to analyze. But those who do, usually pay MUCH bigger money than to web-developers.

Don’t let a lack of experience hold you back from pursuing a data science career… Before I broke into data science, I was constantly learning new things but didn’t have much work experience to show for it. Here’s what I did: 1. Built a portfolio I worked on personal projects to showcase my skills. 2. Joined online communities Networking with others in the field helped me understand the industry better and opened up opportunities. 3. Practiced coding interviews I spent time solving problems and practicing coding challenges. This was crucial in helping me get comfortable with technical interviews. 4. Highlighted my learning journey During interviews, I spoke about my dedication to learning and the projects I completed. ✨ My projects and learning outside of my data Bootcamp landed me my first job. There’s always another way to show your value. Don’t give up easily! P.S. What other strategies have you used to overcome the lack of experience in your job search? #DataSistah ♻️Reshare and help others.

Aspiring Data Scientists shouldn't apply to 100s of jobs... They should only apply for 10. Here's why: You'll have a lot more success if you 1) Choose a sector(s) you want to work in (e.g., healthcare) 2) Build Tailored Projects for those sectors 3) ONLY APPLY FOR JOBS IN THOSE SECTORS With the right Tailored Projects, this plan will make you a good fit for each role you apply for. This means you only need to apply for 10s of jobs, not 100s. So pick jobs you're interested in, build the right Tailored Projects and then apply to relevant roles. What sectors are you keen to work in? Let me know below ⬇

Analyzing My Data Science Portfolio Projects Like many graduates, I did not have a job lined up after earning my data science master’s degree; the reason is because I didn’t apply anywhere. For three months. I graduated in spring time but didn’t begin my job search, in earnest, until summer. Either fear or foresight compelled me to believe I wasn’t ready, and that emotion drove me to invest the hours I wasn’t working an hourly job at a local hotel into crafting a marketable, desirable data science portfolio. When I receive comments and LinkedIn messages with questions related to breaking into the data industry, my first tip is always to create a GitHub-hosted portfolio that you can use as a professional calling card. Bonus points if you create engaging documentation or share that content on a platform like Medium or LinkedIn to connect with…

Hi LinkedIn, Would you be interested in a fulfilling and impactful career in Data Science? Have you wondered what the common pattern is for those who are able to consistently become an authority in their company while others struggle to add value? Sravya Madipalli, Shane Butler, and I are at the early stage of putting together a program to help fellow data professionals break in, advance, and thrive in their career. Many existing resources aimed at helping Data Science professionals generally focus on navigating interviews, often putting heavy emphasis on technical training. However, we believe these resources only scratch the surface. For example, we’ve implemented standard practices and operationalized processes throughout our careers to consistently deliver measurable impact, yet these frameworks are seldom discussed. This program brings collective insights from decades of experience across reputable companies, emphasizing progression through rising seniority. It is rarely about just the technical skills or how quickly one can get tasks done, we believe success in this field can be systematized. We are very early in putting this program together and we’re looking to gauge the level of interest in something like this. If you’re interested in learning more about the program, just wanting to follow along, or becoming a voice in this journey, please join the waitlist below. This will be super helpful for us and thank you in advance. https://lnkd.in/gr6ENsxA If you know of anyone in your network who may benefit, please repost or share the link with them too! 

Are you ready to make a real impact with your data science skills? Join Hai Guan, Sravya Madipalli, and me in shaping a unique program dedicated to practical application and personalized coaching for aspiring and advancing data scientists. • Real-World Scenarios: Tackle practical examples that mirror your everyday challenges. • Adaptive Coaching: Receive personalized guidance that aligns with your specific career goals and the culture at your company. • Strategic Communication: Enhance your ability to communicate data insights across all organizational levels effectively. 💡We’re building this with your input! Help us tailor the program to your needs. Early members gain exclusive access and a chance to influence our content development. https://lnkd.in/gr6ENsxA 🔄 Know someone looking to enhance their data science skills? Please share this post or tag them in the comments! #DataScience #CareerGrowth #RealWorldSkills #ProfessionalDevelopment

Hello friends! Who in my network knows some clever Data Scientists who would be open to sharing insight into their career with some juniors? We are running another virtual career gathering in two weeks and would love your help! It is a tough time out there for juniors. These sessions are a way of creating a safe space for Junior Data Science graduates starting out in their careers to learn from people a few steps ahead. Here's how you can contribute: - Experienced data peeps, if you can spare some time to answer questions asynchronously, drop a note in the comments! - If you know any Data Science grads who might find this useful, feel free to tag them as well - Finally, any recruiters or hiring managers who might be open to sharing some tips would also be highly valuable! Tagging a couple of the legends that helped last time in case they know people who know people who could help, as well as a few others I know who love a bit of data. young ly, Carl Rosati, Nick Botner, Jenny Sahng, Walter Lim, Avinash de Silva, Ben Purcell, Rowan Savage, Minta Holton, Fer Travaglini, Annie Mārama McDougall, Becca O'Shea, Harry Uffindell, Siân Govind, Russ Bennett