AI Consultant - Platform Delivery

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 environments.
• Execute statistical and data modeling techniques (e.g., hypothesis testing, A/B Testing setup, marketing impact analytics, statistical validity etc.) on large datasets 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, perform proforma analysis for estimating business opportunity, and deploy the use case for the clients.
• Collaboration: Work in a cross-functional team environment to lead 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 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, with strong academic performance in analytics and quantitative coursework.
• 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 or 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 algorithms/methodology from scratch and not merely executed existing codes and processes.
• Ability to coach and mentor juniors on the team to drive on-the-job learning & expertise building.