Data Scientist - II

We're looking for a Data Scientist to join Pronto's data team and work on some of the most important problems across our marketplace. You'll work closely with product, engineering, operations, and business teams to turn large amounts of behavioral and operational data into models, insights, and decision systems that directly impact the business. This is not a reporting-heavy role. You'll have the opportunity to work on real-world machine learning and marketplace problems where your work can influence how Pronto operates across cities.

Responsibilities:

• Build models to forecast customer demand and professional supply across cities, neighborhoods, and time periods.
• Develop analytical and ML solutions for supply-demand matching and marketplace optimization.
• Identify the key drivers of customer acquisition, conversion, retention, and repeat behavior.
• Build models to improve professional utilization, activation, and retention.
• Analyze cancellations, no-shows, fulfillment times, and service quality to identify opportunities for improvement.
• Develop pricing, incentive, and promotion models that balance customer experience, professional earnings, and unit economics.
• Design and analyze experiments to evaluate new products, pricing strategies, and operational initiatives.
• Build customer and professional segmentation models to support targeted interventions.
• Partner with Product and Operations teams to convert analytical findings into production-level decisions and business outcomes.
• Establish robust metrics and measurement frameworks for marketplace health.
• Communicate complex analytical findings clearly to senior stakeholders and influence product and business decisions.

Requirements:

• 3-6 years of experience in data science, machine learning, product analytics, or a closely related field.
• Strong proficiency in Python and SQL.
• Strong foundation in statistics, probability, and experimentation.
• Experience building and deploying machine learning models to solve business problems.
• Experience working with large, messy, and high-dimensional datasets.
• Strong understanding of model evaluation, feature engineering, and statistical analysis.
• Experience with A/B testing, causal inference, or experimentation is a strong plus.
• Ability to translate ambiguous business problems into structured analytical or ML problems.
• Strong communication skills and the ability to work effectively with product, engineering, and operations teams.

Good to have:

• Experience working on one or more of: Marketplaces or two-sided platforms, quick commerce, e-commerce, mobility/transportation, logistics, hyperlocal businesses, Consumer internet, demand forecasting, Recommendation or ranking systems, Pricing or incentive optimization, Supply-demand matching, customer lifecycle/retention modelling, Operations research
• Experience with tools such as Spark, Databricks, Airflow, dbt, or cloud data platforms is a plus.