Decision Analytics Consultant - Commercial Analytics + AI Engineering

Posted Yesterday
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Pune, Maharashtra, IND
Hybrid
Senior level
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Where passion changes lives
The Role
Leads AI-enabled analytics engineering and commercial analytics workstreams for life-sciences and other clients. Builds Databricks insight pipelines, agentic LLM workflows, conversational analytics, evaluation harnesses, governed data products, and production-quality software. Structures ambiguous business questions, applies advanced analytical methods, integrates complex data sources, and translates findings into decisions and client-ready deliverables. Manages and coaches teams of 2–4, oversees quality and delivery risks, supports client stakeholders, and contributes to proposals and capability development.
Summary Generated by Built In
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 development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you'll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in India , visit ZS India office locations | Where we work | ZS .
Hybrid working model:
We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.
Travel:
Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.
Considering applying?
At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems-the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. Learn more about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive.
If you're eager to grow, contribute, and bring your unique self to our work, we encourage you to apply.
ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law.
To complete your application:
Candidates must possess or be able to obtain work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered.
NO AGENCY CALLS, PLEASE.
Find Out More At:
www.zs.com

Skills Required

  • Bachelor's or master's degree in engineering, with strong academic performance in analytics and quantitative coursework
  • 5–8 years of relevant job experience; an MBA or PhD may substitute for work experience
  • Expert-level SQL, including window functions, cohort and longitudinal logic, and performance tuning on claims-scale data
  • Production-grade Python experience, including pandas or PySpark, packaging, testing, and Git
  • Experience with a lakehouse platform such as Databricks, Delta, Unity Catalog, and Spark, or comparable Snowflake or BigQuery with Spark experience
  • LLM application engineering experience, including prompt and context engineering, RAG, function or tool calling, agent frameworks, evaluation, and monitoring
  • Applied analytics experience solving business problems in stakeholder-facing roles across multiple analytical methods
  • Statistical rigor and explicit quality-control experience
  • Life-sciences or healthcare analytics experience, including real-world, claims, EHR, registry, clinical, trial, or engagement data
  • Consulting skills, including structuring ambiguity, owning deliverables, and communicating in PowerPoint, Excel, and presentations
  • Experience leading at least two people with accountability for delivery quality
  • Fluency in English
  • Client-first mentality, intense work ethic, collaborative spirit, and problem-solving approach
  • Work authorization for the intended country of employment or ability to obtain it

What the Team is Saying

Ash Easwar
Suzanne Boyan
Kristina Sambucci
Callum Brazier
Michelle Lu
Mike Vula
Mina Labib
Judith Kulich
Anna Simon
Rachana Late
Bazgha Qutab
Ayush Kataria
Carolina Blanco
Kumar Ritwik
Emily Reynolds
Mahmood Majeed
Mahmood Majeed
Bazgha Qutab
Mahmood Majeed

ZS Compensation & Benefits Highlights

  • Healthcare Strength — Healthcare is described as a standout, with low‑cost medical through UMR/UnitedHealthcare, fully covered vision with an eyewear allowance, and mental‑health resources such as Talkspace, Bend Health, and a 24/7 EAP. Dental coverage is detailed as strong as well, including 100% for preventive/basic services and additional support for major and orthodontic care.
  • Parental & Family Support — The package includes 10 weeks of paid family leave and extensive family‑forming support (e.g., Carrot), plus backup childcare/eldercare/pet care and travel support like Milk Stork. These offerings indicate robust support for a wide range of family needs.
  • Leave & Time Off Breadth — Paid time off starts at 15 days from hire and increases to 20 days after 36 months, alongside 11 paid holidays, a floating holiday, and sick time with rollover. This structure signals broad time‑off provisions on paper.

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The Company
HQ: Evanston, IL
15,000 Employees
Year Founded: 1983

What We Do

ZS is a management consulting and technology firm that partners with companies to improve 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. Founded in 1983, ZS has more than 15,000+ employees in over 40 offices worldwide.

Why Work With Us

ZS is home to passionate people who embrace innovative thinking, collaboration and a client-first mindset. Welcome to a company where new ideas are celebrated, curiosity is welcomed, learning opportunities are abundant and colleagues become lifelong connections.

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

The Flexible & Connected model is our ZS standard. ZSers decide where it makes the most sense for them to work each day given client or teamwork.

Typical time on-site: 3 days a week
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HQEvanston (Global HQ)
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