What You'll Do
Deep analytics-tech expertise:
- Develop and implement advanced algorithms that solve complex business problems in a computationally efficient and statistically effective manner leveraging tools like PySpark, Python, SQL on Client/ZS cloud environment.
- Execute statistical and data modeling techniques (e.g., hypothesis testing, A/B Testing setup, marketing impact analytics, statistical validity etc.) on large data sets to identify trends, figures, and other relevant information with scalable and operational process implementations.
- Evaluate emerging datasets and technologies that may contribute to our analytical platform, including a good understanding of Generative AI capabilities and SaaS products.
Communication, collaboration, unstructured problem solving, and client engagement (in a high performing and high intensity team environment):
Problem solving and Client engagement:
- Understand client business priorities, develop product use cases, do proforma analysis for estimating business opportunity, and deploy the use case for the clients.
Collaboration:
- Work in a cross-functional team environment to lead the client engagement and collaborate on holistic solutions comprising best practices from Frontend and Backend engineering, Data Science, and ML Engineering areas.
Storyboarding & impact communication:
- Build effective storyboards to communicate solution impact to clients and ZS Leadership.
Scaling mindset:
- Provide a structure to client engagement, build and maintain standardized and operationalized Quality Checks on team's work, and ensure high quality client deliverables.
Team management:
- Export best practices and learnings to the broader team and mentor Associates on teams.
What You'll Bring
- Bachelor's degree in Computer Science (or Statistics) from a premier institute, and strong academic performance with analytics and quantitative coursework is required.
- Knowledge of programming - Python (Deep Expertise), PySpark, SQL.
- Expertise in machine learning, regression, clustering, and classification models (preferably in a product environment).
- Knowledge of big data/advanced analytics concepts and algorithms (e.g., social listening, recommender systems, predictive modeling, etc.).
- Excellent oral and written communication skills.
- Strong attention to detail, with a value-addition mindset.
- Excellent critical thinking and problem-solving skills.
- High motivation, good work ethic, and maturity.
- 3-5 years of relevant post-collegiate work experience, preferably in industries like B2C, Product companies, in execution roles focused on Data & Decision Sciences, Data Engineering, Stakeholder management, and building scalable processes.
- Should have hands-on analytics experience where the candidate has worked on the algorithms / methodology from scratch and not merely executed existing codes and processes.
- Ability to coach, mentor juniors on the team to drive on-the-job learning & expertise building.
