Manager - Commercial Analytics/Data Science

Job Description:

Organization - Quantzig Analytics

About the Role:

We're hiring a Commercial Analytics Manager to partner with pharmaceutical clients on commercial analytics and data-driven business problems. This is a consulting role at the intersection of pharma commercial domain knowledge, hands-on analytics, and client advisory.

You'll act as a trusted commercial analytics consultant helping clients frame the problem, identify the right data, assess what's available, shape the analytical approach, and translate results into recommendations the business can act on. You'll move fluently from business question to data requirement to analytical approach to rapid POC to insight to recommendation, working effectively with both pharma business stakeholders and technical / data teams.

Experience:

- Min 6+ years

Notice Period - 15 days/Immediate Joiners

Domain: Pharma / Life Sciences

Function: Commercial Analytics

What You'll Do:

- Partner with pharma clients to understand commercial business problems and translate them into clear data and analytics requirements.

- Advise clients on the data sources, datasets, attributes, and level of granularity needed to answer specific commercial questions.

- Assess available datasets and surface gaps, limitations, and opportunities for additional data.

- Define analytical frameworks, KPIs, methodologies, and approaches for commercial use cases.

- Work hands-on with pharmaceutical datasets to explore, validate, and analyze data.

- Build analytical models, prototypes, and proof-of-concepts to demonstrate solutions and align with clients before full-scale development.

- Translate analytical outputs into clear business insights and actionable recommendations.

- Partner with data engineering / technology teams to communicate data requirements and ensure solutions are implementable.

- Lead analytics workstreams and own client discussions, requirements, and deliverables.

- Present approaches and findings to both business and technical stakeholders.

What You'll Bring:

1. Commercial Analytics Depth:

Strong experience in pharmaceutical commercial analytics, with real depth in 2-3 of the following. You need not be an expert across all of them; depth in a few plus broad understanding is what we're after:

- Sales Force & Commercial Effectiveness

- Customer / HCP Analytics

- Patient Analytics / Patient Journey

- Market Access & Payer Analytics

- Omnichannel & Promotional Analytics

- Market & Competitive Analytics

- Forecasting & Scenario Analytics

- Launch Analytics

2. Pharmaceutical Data Experience:

Hands-on experience with one or more of the following, plus a clear sense of what each can and cannot answer, how datasets combine, and what additional data a question may require:

- Claims data

- Prescription / Rx data

- Patient-level data

- HCP / customer data

- CRM / field activity data

- Payer / formulary data

- Market / syndicated data

- Specialty pharmacy / hub data

- Digital / engagement data

3. Technical Skills Required:

- Python

- SQL

- Databricks

- Strong data analysis and statistical reasoning

- Experience with large, complex healthcare or pharmaceutical datasets

4. Technical Skills Preferred:

- Rapid analytical prototyping and vibe coding with modern AI-assisted development tools

- Ability to quickly build lightweight analytical apps, prototypes, or POCs to validate concepts and drive client alignment

- Familiarity with Git / version control

- Exposure to cloud-based data environments

- Power BI / Tableau or equivalent visualization tools

- The goal isn't production-grade software or AI platforms; it's using modern, AI-assisted tools to quickly test, demonstrate, and communicate analytical concepts.

5. Consulting & Client Skills:

- Structuring ambiguous business problems.

- Translating business questions into specific data requirements and analytical approaches.

- Comfort challenging client assumptions and recommending alternatives.

- Strong communication and presentation skills, including explaining technical concepts to non-technical stakeholders.

- Managing client-facing analytics workstreams.

- Working effectively across business, analytics, and technical teams.

The Ideal Candidate:

Combines pharma commercial knowledge + data expertise + hands-on analytics + consulting and can move independently, end to end: Business Question - Data Requirement - Analytical Approach - Rapid POC - Insight - Recommendation