DataZymes - Decision Science Consultant - Python

EXPERIENCE REQUIRED :

- 4+ years of experience in analytics or decision sciences, with a focus on the pharmaceutical industry.

- Demonstrated experience executing analyses and supporting delivery on complex pharma analytics projects.

- Strong expertise in commercial analytics like Market Mix Modelling, Test and Control analytics, OCE analytics, Budget Optimization etc.

- Preferred exposure to Patient analytics, Market Access analytics, or Sales analytics.

- Experience collaborating with cross-functional teams; informal mentoring or peer coaching is a plus.

- Power BI or similar dashboarding experience (e.g., Tableau, Looker) is a plus.

Technical Skills :

- Advanced knowledge of statistical analysis tools and programming languages such as Python, SAS, SQL, etc. along with a strong hold on Microsoft suit

- Strong understanding of AI/ML techniques and their applications in decision sciences.

Communication and Leadership :

- Excellent written and verbal communication; able to translate analyses into crisp, client-ready narratives, collaborate with cross-functional teams, and build strong client relationships.

- Demonstrates ownership and initiative; contributes to thought leadership (POVs, case studies, playbooks)

RESPONSIBILITIES

Delivery & day to day operations :

- Support planning and day-to-day execution of Decision Sciences projects, owning defined workstreams and deliverables.

- Partner with cross-functional teams to clarify objectives, scope, timelines, and resource needs; maintain project trackers and documentation.

- Perform hands-on analytics, data preparation, and QC; flag risks/blocks early and propose practical mitigations.

- Monitor progress against milestones and quality standards to ensure on-time, high-quality delivery.

- Drive the development and enhancement of analytical products and solutions for commercial and marketing analytics.

- Conduct market research and stay updated on industry trends, emerging technologies, and best practices.

- Collaborate with internal stakeholders, including data scientists, software developers, and domain experts, to define product requirements.

- Guide the product development lifecycle, from ideation and prototyping to testing, deployment, and maintenance.

- Design, Develop, and deploy complex and innovative analytical solutions for clients.

Product & Solution Development :

- Contribute to the design and enhancement of analytics solutions for commercial and marketing use cases.

- Stay current on industry trends, tools, and best practices; synthesize learnings into actionable recommendations.

- Build, validate, and help operationalize models, pipelines, and dashboards as part of deployment/deliverables.

- Apply and evaluate statistical/ML techniques relevant to pharma analytics; compare methods for fit, accuracy, and interpretability.

- Design small experiments/POCs, analyze outcomes, and summarize implications for client use.

- Translate methodological findings into clear guidance, POVs, and internal playbooks.