Senior Data Scientist

MathCo; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

MathCo in Bengaluru seeks a Senior Data Scientist with 4–7 years of experience in pharma/Life Sciences commercial analytics. You will develop predictive models, analyze large healthcare datasets, and build dashboards to support sales, marketing, and market access.

Responsibilities include data pipelines, model validation, and collaboration with cross-functional teams. Proficiency in Python or R, SQL, and BI tools is essential; cloud familiarity is preferred.

Qualifications

• Bachelor's or master's in a quantitative field.
• 4–7 years in Data Science with Pharma/Life Sciences commercial analytics.
• Understanding of pharma commercial processes (sales/marketing/customer analytics).
• Hands-on ML, statistical analysis, and predictive modeling.
• Proficiency in Python or R for analysis and modeling.
• Strong SQL for data extraction and manipulation.
• Experience with Tableau or Power BI for visualization.
• Familiarity with cloud platforms (AWS/Azure/GCP) preferred; Agile and Git a plus.

Responsibilities

• Develop predictive and descriptive analytical models for commercial objectives.
• Analyze large healthcare and market data to derive insights.
• Build ML models for segmentation, forecasting, and campaign effectiveness.
• Design data pipelines, feature engineering, and model validation.
• Collaborate with stakeholders to translate business problems into analytics.
• Create dashboards and visualizations to communicate findings.
• Monitor model performance and iterate improvements.

Skills

Python

SQL

R

Machine Learning

Statistical Modeling

Data Visualization

Spark

Databricks

Cloud Platforms

Git

Education

Bachelor's or master's degree in data science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline

Tools

Tableau

Power BI

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)