Decision Analytics Consultant - Commercial Analytics + AI Engineering

ZS

Pune District

Hybrid

INR 4,000,000 - 8,500,000

Full time

2 days ago
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Job summary

ZS is a leading management consulting and technology firm focused on analytics for patients, caregivers, and consumers. This role centers on building AI-enabled analytics products, leading build pods, and independently owning core analytics problems for client teams.

You will split time between AI/analytics engineering and core commercial analytics, guiding 2–4 associates and collaborating with enterprise-AI stakeholders across client engagements.

Qualifications

  • Bachelor’s or master’s degree in engineering with analytics emphasis.
  • Strong analytics and quantitative coursework with high academic performance.
  • Experience in healthcare or life sciences analytics is a plus.

Responsibilities

  • Own end-to-end build of insights pipelines on Databricks: Delta tables to KPI surfaces.
  • Design agentic workflows using an SDK, including context, prompts and governance.
  • Enforce data guardrails and governance across surfaces and prompts.
  • Build evaluation harnesses for LLM outputs and release gates.
  • Deliver NL-to-SQL analytics on governed semantic layers with KPI definitions.
  • Establish engineering standards: code review, CI, tests, release notes.
  • Produce architecture docs, security evidence, and status reporting.
  • Lead 2+ associates; manage delivery risk and client-facing workstreams.

Skills

SQL expert
Python production-grade
Databricks Lakehouse
LLM application engineering
Applied analytics
Consulting skills
People leadership
English fluency
Client-first mentality

Education

Bachelor's or master's in engineering

Tools

Databricks / Delta / Unity Catalog
Spark
Snowflake
BigQuery
Git

Job description

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS.

Insights & Analytics

ZS's Insights & Analytics group partners with clients to design and deliver solutions to help them tackle a broad range of business challenges. Our teams work on multiple projects simultaneously, leveraging advanced data analytics and problem-solving techniques. Our recommendations and solutions are based on rigorous research and analysis underpinned by deep expertise and thought leadership.

The role

A build-and-advise role. You lead build pods on AI-enabled analytics products and independently own core commercial analytics problems for the same client teams. Expect roughly a 60/40 split between AI engineering and core analytics, flexing with the release cycle. You own workstream-level delivery, manage 2 - 4 Associates / Associate Consultants, and are the day-to-day technical counterpart for client analytics and enterprise-AI stakeholders.

This is not a pure AI/ML engineering role. When build demand is low, you are staffed on core analytics workstreams for the same client; when it is high, you lead the build. Both halves are required.

What You'll Do
AI & analytics engineering (~60%)
  • Own end-to-end build of insight pipelines on Databricks: certified Delta tables → metric layer → signal detection → LLM narrative → application surface.
  • Design agentic workflows on an agent SDK (Claude Agent SDK or equivalent): tool design, context and prompt engineering, governed context stores, fallbacks and failure handling.
  • Enforce guardrails in data and metadata - governed tables, SQL-level scope control - rather than in prompt instructions.
  • Build evaluation harnesses for LLM output: answer-quality rubrics, binary gates (numerical fidelity, grounding, compliance), regression suites, release gates; tracing via Langfuse/LangSmith or equivalent.
  • Deliver conversational analytics (NL-to-SQL) on governed semantic layers (Databricks Genie, Metric Views) with certified KPI definitions.
  • Set engineering standards: code review, Git/CI, unit and SIT test plans, UAT support, release notes, observability, cost and latency tracking.
  • Produce architecture documents, security / IT-risk evidence packs and status reporting with honest status legends (implemented / in-flight / planned / blocked).
Core commercial analytics (~40%)
  • Take ambiguous questions from any client function - commercial, medical, market access, clinical development, supply chain, enterprise operations - and structure them into decision-oriented analytical plans; own them end to end.
  • Pick the method the question needs - diagnostic analysis, cohort and longitudinal analysis, segmentation, forecasting, test-and-control and causal inference, predictive modelling, optimisation - and defend the choice.
  • Work across the client's data estate - syndicated and patient-level real-world data, clinical and trial data, engagement and CRM data, payer and access data, operational and financial data - integrating sources and resolving definitional conflicts.
  • Establish governed definitions (KPIs, cohorts, business rules) with the client and make them enforceable in code - one definition, every surface.
  • Convert results into decisions: QC'd, client-ready narratives and decks; activation into workflows, dashboards or products; present to Director+ stakeholders.
Client & team leadership
  • Plan, review and coach a team of 2 - 4; QC everything before it reaches the client.
  • Own workstream status, risks and dependencies with ZS leadership and client PMO.
  • Contribute to proposals, POVs and CST capability building - reusable assets and AI upskilling of CST talent.
What You'll Bring
  • A bachelor’s or master’s degree in engineering (any discipline) with strong academic performance, particularly in analytics and quantitative coursework
  • 5 - 8 years of relevant job experience. An MBA/PhD may substitute in lieu of work experience
  • SQL - expert. Window functions, cohort and longitudinal logic, performance tuning on claims-scale data.
  • Python - production-grade. pandas/PySpark, packaging, testing, Git; you have owned code others depend on.
  • Lakehouse platform - Databricks (Delta, Unity Catalog, Spark, Workflows) or comparable (Snowflake/BigQuery + Spark).
  • LLM application engineering - Prompt and context engineering, RAG, function/tool calling, agent frameworks (Claude Agent SDK, LangGraph or equivalent), evaluation and monitoring. You can explain how your system failed and what you changed.
  • Applied analytics - solving business problems in a stakeholder-facing role, spanning more than one method family: diagnostic and cohort/longitudinal analysis, segmentation, test-and-control / causal inference, forecasting, predictive modelling; statistical rigour and explicit QC. Life-sciences or healthcare analytics experience strongly preferred - any function (commercial, medical, market access, clinical development, operations); hands-on with real-world data (claims, EHR, registries), clinical/trial or engagement data a plus.
  • Consulting skills. Structure ambiguity, own deliverables end to end, communicate crisply in PowerPoint, Excel and in the room.
  • People leadership. Has led 2+ people on delivery with accountability for their output quality.
  • Fluency in English
  • Client-first mentality
  • Intense work ethic
  • Collaborative spirit and problem-solving approach
How you'll grow:
  • Cross-functional skills development & custom learning pathways
  • Milestone training programs aligned to career progression opportunities
  • Internal mobility paths that empower growth via s-curves, individual contribution and role expansions
Perks & Benefits:

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional

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