Data Science

Weekday; Mumbai; On-site; INR 1,100,000 - 1,600,000; Full time

Job summary

Weekday is seeking an Analytics Professional in Mumbai to strengthen analytics capabilities, develop scalable data solutions, and generate actionable insights for business growth. The role combines data analytics, predictive modelling, experimentation, data infrastructure, and BI to address customer acquisition, retention, risk, delinquency, and profitability.

You will build and maintain scalable data pipelines, deploy predictive models, and collaborate with cross-functional teams to run

Qualifications

• 2+ years of hands-on analytics experience in fintech, financial services, startups, consulting, or a related environment.
• Strong proficiency in SQL and Python for data analysis, querying, modelling, and automation.
• Strong understanding of data-driven problem solving and analytical frameworks.
• Experience working with large datasets and converting complex data into actionable business insights.
• Hands-on experience with data management, deployment, monitoring, and performance management frameworks.
• Understanding of predictive modelling, scoring systems, and analytical decision-making.
• Exposure to A/B testing, experimentation, or test-and-learn methodologies.
• Experience working with data warehouses, data marts, reporting systems, and analytical infrastructure.
• Strong understanding of data quality, consistency, validation, and reliability.
• Ability to connect analytical findings with measurable business outcomes.
• Strong communication and stakeholder-management skills, with the ability to explain analytical concepts clearly.
• Highly analytical, detail-oriented, and comfortable investigating complex business problems.
• Self-driven and proactive, with the ability to work independently in a fast-paced, data-driven environment.
• Strong problem-solving mindset and willingness to continuously learn new analytical techniques and technologies.

Responsibilities

• Define, manage, and continuously improve the analytics roadmap in alignment with business objectives.
• Build, deploy, and maintain scalable data infrastructure, including data warehouses and data marts.
• Develop and maintain predictive models, scoring systems, and analytical solutions to support business decisions.
• Explore and evaluate alternate data sources to improve predictive capabilities and business insights.
• Work with large and complex datasets to identify trends, patterns, opportunities, and business risks.
• Partner with cross-functional teams to design and execute A/B tests, experiments, and test-and-learn initiatives.
• Develop analytics solutions supporting customer acquisition, churn reduction, delinquency control, and profitability improvement.
• Generate actionable insights through automated reports, dashboards, MIS, analytical queries, and business intelligence solutions.
• Monitor model performance, business metrics, data quality, and analytical outputs.
• Identify performance gaps and recommend optimisation strategies based on data-driven analysis.
• Ensure data accuracy, consistency, reliability, and availability across reporting and analytics systems.
• Support deployment, monitoring, and performance management of analytical and predictive solutions.
• Develop reusable analytical frameworks and processes to improve efficiency and scalability.
• Collaborate with stakeholders to understand business requirements and translate them into analytical solutions.
• Present analytical findings and recommendations clearly to technical and non-technical stakeholders.
• Continuously identify opportunities to improve analytics processes, automation, data utilisation, and decision-making.

Skills

SQL

Python

Data analysis

A/B testing

BI/Reporting

Stakeholder management

Problem solving

Tools

Data warehouses

Data marts

ETL pipelines

Python data libraries

Job description

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Experience: 2+ yrs

Location: Mumbai, Maharashtra, India

Job Type: Full-time

We are looking for an analytical and data-driven Analytics Professional to strengthen analytics capabilities, develop scalable data solutions, and generate actionable insights that support business growth and informed decision-making.

The role combines data analytics, predictive modelling, experimentation, data infrastructure, and business intelligence, offering an opportunity to work on high-impact business problems across customer acquisition, retention, risk, delinquency, and profitability.

Requirements

Key Responsibilities

• Define, manage, and continuously improve the analytics roadmap in alignment with business objectives.
• Build, deploy, and maintain scalable data infrastructure, including data warehouses and data marts.
• Develop and maintain predictive models, scoring systems, and analytical solutions to support business decisions.
• Explore and evaluate alternate data sources to improve predictive capabilities and business insights.
• Work with large and complex datasets to identify trends, patterns, opportunities, and business risks.
• Partner with cross-functional teams to design and execute A/B tests, experiments, and test-and-learn initiatives.
• Develop analytics solutions supporting customer acquisition, churn reduction, delinquency control, and profitability improvement.
• Generate actionable insights through automated reports, dashboards, MIS, analytical queries, and business intelligence solutions.
• Monitor model performance, business metrics, data quality, and analytical outputs.
• Identify performance gaps and recommend optimisation strategies based on data-driven analysis.
• Ensure data accuracy, consistency, reliability, and availability across reporting and analytics systems.
• Support deployment, monitoring, and performance management of analytical and predictive solutions.
• Develop reusable analytical frameworks and processes to improve efficiency and scalability.
• Collaborate with stakeholders to understand business requirements and translate them into analytical solutions.
• Present analytical findings and recommendations clearly to technical and non-technical stakeholders.
• Continuously identify opportunities to improve analytics processes, automation, data utilisation, and decision-making.

What Makes You a Great Fit

• 2+ years of hands-on analytics experience in fintech, financial services, startups, consulting, or a related environment.
• Strong proficiency in SQL and Python for data analysis, querying, modelling, and automation.
• Strong understanding of data-driven problem solving and analytical frameworks.
• Experience working with large datasets and converting complex data into actionable business insights.
• Hands-on experience with data management, deployment, monitoring, and performance management frameworks.
• Understanding of predictive modelling, scoring systems, and analytical decision-making.
• Exposure to A/B testing, experimentation, or test-and-learn methodologies.
• Experience working with data warehouses, data marts, reporting systems, and analytical infrastructure.
• Strong understanding of data quality, consistency, validation, and reliability.
• Ability to connect analytical findings with measurable business outcomes.
• Strong communication and stakeholder-management skills, with the ability to explain analytical concepts clearly.
• Highly analytical, detail-oriented, and comfortable investigating complex business problems.
• Self-driven and proactive, with the ability to work independently in a fast-paced, data-driven environment.
• Strong problem-solving mindset and willingness to continuously learn new analytical techniques and technologies.