Senior Data Scientist

MathCo; Bengaluru Urban; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

MathCo in Bangalore is seeking a Senior Data Scientist with 4–7 years in pharma or life sciences analytics to drive commercial insights using advanced analytics and ML. You will build predictive models, design data pipelines, and collaborate with cross-functional teams to support sales, marketing and market access decisions.

The role involves delivering dashboards and actionable recommendations, while ensuring data quality and governance in a fast-paced environment.

Qualifications

• Pharma or life sciences analytics experience preferred.
• Strong Python/R and SQL for analysis and modeling.
• Experience with BI tools and cloud platforms.
• Ability to translate business problems into analytical solutions.

Responsibilities

• Develop predictive and descriptive models for commercial objectives.
• Analyze healthcare and market data to derive insights.
• Build ML models for segmentation, forecasting and campaign impact.
• Design data pipelines, feature engineering, and validation.
• Create dashboards to communicate findings.
• Collaborate with cross-functional teams and ensure data governance.

Skills

Python

SQL

R

Machine Learning

Statistical Modeling

Data Visualization

Education

Bachelor's or Master's in Data Science/CS/Statistics/Engineering

Tools

Tableau

Power BI

Spark

Databricks

AWS/Azure/GCP

Job description

Job Role: Senior Data Scientist

YOE: 4-8 yrs

NP: 30 Days only

Location: Bangalore

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.

Technical Skills:

• Python (Pandas, NumPy, Scikit-learn)
• SQL
• R (preferred)
• Machine Learning
• Statistical Modeling
• Data Visualization (Tableau/Power BI)
• Spark or PySpark (preferred)
• Databricks (preferred)
• Cloud Platforms (AWS, Azure, or GCP)