Deep analytics-tech expertise:
- Develop and implementadvanced algorithmsthat solve complex business problems in a computationally efficient and statistically effective mannerleveraging tools like PySpark, Python, SQLon Client/ZS cloud environment
- Executestatistical and data modelling techniques(eg 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.
- Evaluatingemerging datasets and technologiesthat may contribute to our analytical platform including 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 solvingand 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 of best practices from Frontend and Backend engineering, Data Science, and ML Engineering area.
- 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 ensuring high quality client deliverables
- Team management: Export best practices and learnings to broader team and mentor Associates on teams
What you'll Bring:
- Bachelors 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 (eg 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
