Decision Analytics Consultant - Commercial Analytics + AI Engineering
ZS (company site, opens in a new tab)5–8 yrsPuneRemoteDirect career pageEst. 20–35 LPA
Posted 1d ago
Reach people at ZS
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at ZS you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead build pods for AI-enabled commercial analytics products with 60% focus on AI engineering and 40% on core analytics for a single client.
- Own end-to-end delivery of insight pipelines on Databricks and agentic workflows using agent SDKs like Claude Agent SDK, managing technical standards and quality.
- Manage and coach 2–4 associates, handle workstream status and risks, and deliver client-ready narratives and presentations to senior stakeholders.
Minimum Requirements
- Bachelor’s or Master’s degree in engineering with strong analytics/quantitative background.
- 5–8 years relevant experience; MBA/PhD may substitute for experience.
- Expert SQL skills including window functions and performance tuning on large data; production-grade Python experience with pandas/PySpark and Git.
- Experience with Databricks or comparable lakehouse platforms, LLM application engineering including prompt/context engineering, and applied commercial analytics methods.
- Experience leading 2+ people on delivery with full accountability.
- Fluency in English and ability to travel as needed.
Ideal Candidate Profile
- Senior analytics professional comfortable balancing AI engineering build and core commercial analytics ownership within life sciences or healthcare domains.
- Operates in highly technical, stakeholder-facing roles requiring end-to-end ownership from data engineering to delivery and client communication.
- Experienced in managing small teams, setting engineering standards, and handling complex, multi-source data ecosystems for decision-oriented analytics.