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Decision Scientist with 1+ years in data analytics, real-world evidence (RWE), and health economics
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Outcome-oriented Decision Scientist with 1+ years of client-facing experience in data analytics, specializing in real-world evidence (RWE) and health economics and outcomes research (HEOR), delivering actionable insights and optimizing budgets and processes for Fortune 100 pharmaceutical companies.
Visvesvaraya Technological University
Bachelor of Engineering · Computer Science
August 1, 2020 – June 30, 2024
Adarsh Vikash Vidyalaya
Higher Secondary School
June 1, 2018 – May 31, 2020
Mu Sigma Inc.
Decision Scientist
August 1, 2024 – July 1, 2025
Bengaluru, Karnataka, India
Intel Corporation
Industrial Trainee
May 1, 2023 – July 1, 2023
Bengaluru, Karnataka, India
SigMax Pharma: Predictive HR Analytics for Employee Retention
June 18, 2026 – Present
Built the muPDNA framework to define the problem and uncover key attrition drivers. Performed EDA, model training, and supported deliverables like ADF, BPF, and reports. Designed Figma mockups and developed a Power BI dashboard to visualize attrition risk. Collaborated on building predictive models to flag high-risk employees and guide retention strategy.
RWE Study: VTE and Bleeding Risk in TIA/IS Patients on Anti-Platelet Therapy
June 18, 2026 – Present
Conducted an observational study using MarketScan data to evaluate VTE and bleeding risks in TIA/IS patients on anti-platelet therapy (Clopidogrel vs. Non-Clopidogrel). Developed cohort definitions, applied inclusion/exclusion criteria, and calculated incidence rates using SQL and SAS. Delivered real-world evidence insights by analyzing treatment patterns, discontinuation, switching, and comorbidities across patient cohorts. Generated outcome metrics and descriptive stats to support safety profiling and HEOR deliverables.
Cultural Fit Analysis
The candidate's project diversity, ranging from RWE studies in healthcare to predictive HR analytics, indicates adaptability and a broad interest in applying data science across different domains. Their academic background in Computer Science combined with practical experience in data analytics and decision science aligns well with a data-driven culture. The experience with client-facing roles and team collaboration further supports a good cultural fit for an organization valuing teamwork and stakeholder engagement.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills, client communication, and a team-oriented approach through project descriptions and work experience. Their involvement in collaborative projects and stakeholder engagement indicates good operational fit for roles requiring cross-functional interaction. The use of frameworks like muPDNA suggests a structured approach to problem-solving.