Senior Data Scientist

MathCo; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

MathCo in Bengaluru/India seeks a Senior Data Scientist with 4–7 years in Pharma/Life Sciences Commercial Analytics to drive advanced analytics, predictive modeling and data-driven decision support for sales, marketing and market access. You will build ML models, analyze large healthcare datasets, and collaborate with cross-functional teams to deliver actionable insights.

The role emphasizes Python/R, SQL, Tableau/Power BI, and cloud familiarity (AWS/Azure/GCP) with Agile practices.

Qualifications

• Bachelor's or Master's in data science, statistics, CS, math, engineering or related quantitative discipline.
• 4–7 years of Data Science experience with Pharma/Life Sciences Commercial Analytics.
• Strong understanding of pharmaceutical commercial processes including sales, marketing, customer analytics and market performance measurement.
• Hands-on experience with ML algorithms, statistics and predictive modeling.
• Proficiency in Python or R for data analysis and model development.
• Strong SQL skills for data extraction and manipulation.
• Experience with data visualization tools such as Tableau or Power BI.
• Familiarity with cloud platforms (AWS, Azure or GCP) is preferred.
• Understanding of Agile and Git is an advantage.

Responsibilities

• Develop predictive and descriptive analytical models to support commercial objectives.
• Analyze healthcare, pharmaceutical, sales, claims, Rx, patient and market data for insights.
• Build ML and statistical models for segmentation, targeting, forecasting, next best action and campaign effectiveness.
• Design data pipelines, feature engineering and model validation processes.
• Collaborate with commercial stakeholders to translate business problems into analytics solutions.
• Create dashboards and visualizations to communicate findings using BI tools.
• Monitor model performance and propose improvements based on business feedback.
• Work with cross-functional teams including data engineering and commercial excellence.

Skills

Python

R

SQL

Machine learning

Data analysis

Education

Bachelor's or Master's in quantitative field

Tools

Tableau

Power BI

AWS

Azure

GCP

Git

Job description

We are looking for a highly motivated Senior Data Scientist with 4–7 years of experience in the pharmaceutical or life sciences domain, specializing in commercial analytics. The ideal candidate will leverage advanced analytics, statistical modeling, and machine learning techniques to generate actionable insights that support commercial decision-making, including sales, marketing, market access, and customer engagement.

Key Responsibilities:

• Develop predictive and descriptive analytical models to support commercial business objectives.
• Analyze large-scale healthcare, pharmaceutical, sales, claims, prescription (Rx), patient, and market data to uncover business insights.
• Build machine learning and statistical models for customer segmentation, targeting, forecasting, next best action, and campaign effectiveness.
• Design and implement data pipelines, feature engineering, and model validation processes.
• Collaborate with commercial stakeholders to translate business problems into analytical solutions.
• Create dashboards and visualizations to communicate findings effectively using BI tools.
• Monitor model performance and recommend improvements based on business feedback.
• Work with cross-functional teams including data engineering, business consulting, and commercial excellence teams.
• Ensure data quality, documentation, and adherence to data governance standards.

Required Qualifications:

• Bachelor's or master's degree in data science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.
• 4–7 years of experience in Data Science with a focus on Pharma or Life Sciences Commercial Analytics.
• Strong understanding of pharmaceutical commercial processes, including sales analytics, marketing analytics, customer analytics, and market performance measurement.
• Hands‑on experience with machine learning algorithms, statistical analysis, and predictive modeling.
• Proficiency in Python or R for data analysis and model development.
• Strong SQL skills for data extraction and manipulation.
• Experience with data visualization tools such as Tableau or Power BI.
• Familiarity with cloud platforms (AWS, Azure, or GCP) is preferred.
• Understanding of Agile methodologies and version control tools such as Git is an advantage.