The third edition in C1 Connect’s Summer Webinar series Data Science @ Work x Twitter, featured Jigyasa Grover, Machine Learning Engineer-Ads Prediction on July 2nd.
Hundreds of data professionals and aspiring data professionals joined the session to learn more about Jigyasa’s career journey including her education, how she became one of the youngest published contributors to the Open Source Initiative, and different internships and conferences that ultimately brought her to the Machine Learning Engineering team at Twitter.
Jigyasa also highlighted how she gave back to the community and shared her knowledge with a broader audience by joining initiatives such as Women Who Code, Women Technical, United Nations Initiatives, Google Code-In, Women Machine Learning in Data Science and how joining such initiatives helped build a strong personal network. Most recently, she was a mentor in Correlation One’s DS4A Women’s Summit Program where she assisted a group of enthusiastic female data scientists with their capstone projects, gave advice by sharing her previous experiences, and built a personal relationship with them through a shared professional experience.
Before she opened the floor to questions, Jigyasa shed light on what a day looks like for a Machine Learning Engineer at Twitter: “Each day is very very different as a Machine Learning Engineer-- some days it’s just endless exploration of data and feature engineering, some days we try to build a model from scratch [..] also, set up experiments and keep up with the latest research to incorporate those into our models”
Some questions from the audience included:
- How is your work divided between research and coding?
- What are the most important soft skills that a Machine Learning Engineer should focus on?
- When is a good time in your career to transition from building foundational skill sets to becoming a true specialist?
- Where can I start from to explore more about Machine Learning and gear my career towards this role?
We invite you to watch the full video of Jigyasa’s talk above. If you would like to join a future Data Science @ Work session, feel free to follow C1 on Linkedin or join one of our Data Science for All communities on Meetup.
If you are interested in opportunities at Twitter, please apply to C1 Connect here.
About Data Science @ Work
There is a transparency problem in the data talent market.
At C1 we work with thousands of data scientists, data analysts, and data engineers from around the world, and we often hear from job candidates that they are unsure how to evaluate different data career paths, do not know what skills they should focus on developing, and need some guidance on how to find their next data science job.
Across industries, companies are challenged to define the difference between a great data scientist, data analyst, and data engineer on job descriptions. This makes it difficult for candidates to understand what their day-to-day responsibilities will be, how certain jobs will impact their career trajectories, and how common job titles like ‘data scientist’ differ from one company to another.
This lack of transparency leads to a huge waste of time for both candidates and companies. Candidates adopt ‘spray and pray’ job application strategies, applying to hundreds of roles that have ‘data’ in their title. Talent teams are then forced to search through thousands of resumes to find great candidates who then must be triaged to the appropriate role search. Oftentimes, the interview process uncovers that though a candidate is an excellent data scientist, her goals and skills do not align with the role. This wastes the time of the applicant and Senior Data Scientists responsible for conducting late stage technical interviews.
We launched the C1 Connect Data Science @ Work webinar series to break down the communication barriers between hirers and the world’s best data scientists, data analysts, and data engineers. Each week, our C1 Connect community is invited to hear directly from data leaders who share background on their career journeys, what working in their industry means practically for data professionals, and some tips for navigating the job search (and if applicable, how they can pursue opportunities with their teams).
After each session, candidates are invited to raise their hand for feature opportunities on C1 Connect by sharing their C1 Connect Datafolios- brief profiles designed to communicate the skills, roles, aspirations, and project work specifically for data professionals. Using C1 Connect’s Talent Match Algorithm, we pass on qualified candidates who fit the profile for active opportunities to the proper next steps in the candidate selection process.