Job
Description
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 modelling 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. Evaluating emerging datasets and technologies that 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 (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
