Data Science @ Work x ZS Associates

On Thursday, August 13th, Correlation One hosted the eighth edition of the C1 Connect Data Science @ Work series featuring Sharayu Rane, Data Science Consultant for ZS.

Our 400+ RSVPs came from 5 continents and over 15 different time zones to learn more about Sharayu's career path, how data science is applied in the professional services space, and what opportunities are currently available at ZS.

ZS is a professional services firm with over 35 years of experience bringing deep expertise, an entrepreneurial spirit, and a collaborative approach to today's toughest business challenges. Today, ZS has over 7000 employees across 25+ offices globally who support clients large and small across all industries.

At ZS, Sharayu works with clients to identify business projects that can benefit from advanced data techniques and helps client stakeholders implement these solutions. Her expertise lies in statistical modeling, deep learning and operationalizing AI across industries. In addition to her technical skills, Sharayu relies on her understanding of business goals and priorities to help clients understand what they can do with data and how this will help them succeed in the near and long term.

Sharyu joined us virtually from ZS's office in Pune, India at 10:30pm local time to share how she navigated her data science career and what skills have translated to her on-the-job success. Sharyu studied Electronics and Communications Engineering and had the opportunity to specialize in data science, machine learning, and computer vision before starting her career as Decision Analytics Associate with ZS in 2014. As she has ascended the ranks of ZS's data organization, she's helped others along the way by sharing practical tips and tricks on her blog, Datascienceninja.com.

On any given day, Sharayu and her team can be helping a pharmaceutical firm apply data science to their research and development process, working with a hospitality company to optimize product development and go-to-market strategy, or advising a high tech company on how to improve its customer experience by creating a personalized product recommender, for example. To make Data Science and AI work across these disparate settings, ZS needs to bring together the right problems, talent ecosystem, data, and tech stack.

Sharayu's role is unique compared to past speakers in the Data Science @ Work series as she is challenged to apply advanced analytics to a wide array of problems for clients from very different industries. To be successful, Sharyu must focus on solutions that directly impact her clients goals which means she must use excellent judgment when selecting what types of solutions to implement. In this context, Sharayu's success is dependent on her ability to educate stakeholders on the different data science solutions her team can implement and work collaboratively to pick the right solution for the problem at hand. Oftentimes, her success is equally dependent on her 'soft skills' as it is her technical expertise.

Prior to answering questions from the audience, Sharyu shared some background on what makes a great candidate for ZS's current openings for AI Scientists and Data Science Consultants. At Correlation One, we were particularly excited to see ZS's emphasis on candidates who are strong 'Right Brain' and 'Left Brain' thinkers. Anecdotally, we find most candidates are over-indexed on their technical skills improvement when embarking on their careers in data science. Candidates who fail to develop skills like Emotional Intelligence and Intuitive Thought are doing themselves a disservice. For example, the most sophisticated and theoretically accurate Machine Learning model is worthless to a company if it does not fit within the context of the business or if it is too complex for non-technical stakeholders to understand.

Watch the full Webinar below to hear Sharayu's full remarks on the above as well as the answers to these questions from our audience:

• How does the day-to-day workflow of a Data Science Consultant differ from a Data Scientist who only works on her company's problems?
• How can a candidate display her 'Right Brain Thinking' ability during the recruitment process?
• How specialized should a data scientist become? Should Data Scientists focus on improving general data science skills or should they specialize in one particular area?
• When you were applying for your first job at ZS, what was the interview process like?

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.com.

If you are interested in new data science opportunities at ZS, you can 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.