Decision Science Consultant

Job Description

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.