Data Scientist

Swish; Bengaluru; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Swish in Bengaluru is building the next generation of on-demand food delivery through data-driven product improvements. As a Data Scientist, you will partner with Product, Engineering, and Operations to turn complex data questions into scalable solutions.

You will own problems end-to-end—from framing the business question and exploring data to building models, running experiments, and delivering measurable impact.

Qualifications

• 2–4 years of experience in Data Science, ML, Analytics, or a related field.
• Strong Python and SQL skills with large datasets.
• Experience with regression, classification, time-series forecasting, or recommender systems.
• Ability to translate ambiguous business problems into structured analytical solutions.

Responsibilities

• Develop statistical and machine learning models to solve business and product problems.
• Analyse large datasets to identify trends, patterns, and opportunities.
• Build predictive models for demand forecasting, customer behaviour, delivery operations, and business performance.
• Design and analyse A/B tests and experiments to evaluate product and business decisions.
• Work with cross-functional teams to translate business problems into data-driven solutions.
• Build dashboards, reports, and analytical frameworks to support decision-making.
• Perform exploratory data analysis and communicate insights clearly to stakeholders.
• Monitor model performance and continuously improve existing models.
• Collaborate with Data Engineering and Product teams to ensure reliable data pipelines and deployment of analytical solutions.
• Identify opportunities to automate processes and improve operational efficiency through data and ML.

Skills

Python

Pandas

NumPy

Scikit-learn

SQL

Statistics

Experimentation

Data Visualization

Communication

Problem Solving

Tools

Spark

Airflow

ML Deployment

Job description

Swish is building the next generation of food delivery by owning the entire value chain, from menu design and pricing to kitchen operations and customer experience. Backed by leading investors, we're building the future of food delivery by continuously launching new products, expanding into new markets, and creating innovative operating models.

As a Data Scientist, you will work closely with Product, Engineering, Operations, and Business teams to turn complex data into actionable insights and scalable solutions. You will own problems end-to-end - from understanding the business question and analysing data to building models, running experiments, and measuring impact.

Key Responsibilities

• Develop statistical and machine learning models to solve business and product problems.
• Analyse large datasets to identify trends, patterns, and opportunities.
• Build predictive models for areas such as demand forecasting, customer behaviour, delivery operations, and business performance.
• Design and analyse A/B tests and experiments to evaluate product and business decisions.
• Work with cross-functional teams to translate business problems into data-driven solutions.
• Build dashboards, reports, and analytical frameworks to support decision-making.
• Perform exploratory data analysis and communicate insights clearly to stakeholders.
• Monitor model performance and continuously improve existing models.
• Collaborate with Data Engineering and Product teams to ensure reliable data pipelines and deployment of analytical solutions.
• Identify opportunities to automate processes and improve operational efficiency through data and ML.

What We're Looking For

• 2-4 years of experience in Data Science, Machine Learning, Analytics, or a related field.
• Strong proficiency in Python and experience with libraries such as Pandas, NumPy, Scikit-learn, etc.
• Strong SQL skills and experience working with large datasets.
• Good understanding of statistics, probability, hypothesis testing, and experimentation.
• Hands-on experience building and evaluating machine learning models.
• Experience with regression, classification, clustering, time-series forecasting, or recommendation systems.
• Strong analytical and problem-solving skills.
• Ability to translate ambiguous business problems into structured analytical solutions.
• Strong communication skills and ability to explain technical concepts to non-technical stakeholders.
• Experience working in a fast-paced startup, consumer internet, e-commerce, food-tech, quick-commerce, or marketplace environment is a plus.

Good to Have

• Experience with demand forecasting, pricing, recommendations, customer segmentation, or optimisation.
• Exposure to cloud platforms such as AWS/GCP/Azure.
• Experience with ML deployment, model monitoring, or MLOps.
• Familiarity with Spark, Airflow, or similar data/ML tools.
• Experience working with experimentation frameworks and product analytics.