We are seeking a highly skilled and hands-on Senior Data Scientist with strong foundations in machine learning, statistical modeling, and optimization. This role will focus on designing, building, and deploying scalable analytical and machine learning solutions that drive data-driven decision-making across business functions.
You will partner closely with business, and engineering teams to turn complex data into actionable insights and recommendations that drive profitable, sustainable growth. This is a high-impact role where your work will directly influence commercial decisions, customer engagement, and overall business growth.

Design and implement scalable machine learning solutions using techniques such as regression, classification, time-series forecasting, clustering, and optimization.
Develop simulation engines and scenario-planning tools to guide strategic revenue decisions.

Data Strategy & Engineering Collaboration
Collaborate closely with data engineering teams to design robust data pipelines and feature engineering workflows.
Work with structured and unstructured large-scale datasets from multiple sources (transactional systems, external datasets, digital platforms, etc.).
Support model deployment and lifecycle management in production environments.

Identify high-impact opportunities where machine learning, automation, and optimization can drive measurable value.
Mentor junior data scientists and analysts; Drive innovation by evaluating new modeling techniques, data sources,



and tools to enhance solution capabilities.
Master's or PhD in Data Science, Statistics, Computer Science, Economics, Applied Mathematics, or related field.
~5–8+ years of experience building predictive models and deploying analytical solutions in production environments.
~ Strong expertise in classical machine learning methods and statistical modeling techniques.
~ Strong fluency in Python/R , SQL, and machine learning frameworks (scikit-learn, TensorFlow, PyTorch, Prophet, Stan/PyMC, etc.).
~ Ability to communicate complex concepts to non-technical audiences and influence executive-level stakeholders.
~ Experience deploying models in production environments and working with cloud platforms (AWS/Azure/GCP)

Experience in pricing analytics, revenue management, promotion modeling, trade optimization, or related commercial analytics domains.
Experience working with syndicated retail data (e.g., Nielsen, IRI), POS data, or loyalty datasets.
Knowledge of containerization, MLOps, or modern data stack tools (Databricks, dbt, Airflow).

Opportunity to shape data-driven RGM solutions used across global CPG organizations.
A team-oriented environment with strong partnerships across product, engineering, and commercial teams.
Work on high-impact projects that directly influence revenue and profitability.
Competitive compensation, growth opportunities, and a culture that values innovation and analytical excellence.

📌 Data Science Data Science Data Modeler (Remote) (Bengaluru)
🏢 Asper.ai
📍 Bengaluru