- Exposure to challenging problems across multiple domains

- Ability to directly implement solutions and see them in action; critical partner for all decision-making in the organisation

- Interact with people from various backgrounds - a mix of Statisticians, Consultants, and Programmers

- Flat organization structure with open and direct culture 6. Merit-based fast-growth environment

- Market-leading compensation and benefits

What do you need to have ?

- Bachelor's degree in Business Administration, Engineering, Economics, Finance, Mathematics, Statistics, or a related quantitative field

- Minimum 2 yrs of core Analytics experience.

- Experience in analytics/data science or related field

- Hands-on experience on data manipulation tools like SQL, R, Python, Excel etc.

- Exposure to BI Platforms like Power BI, Tableau etc.

- Knowledge of basic statistical measurement frameworks (measures of central tendency, dispersion, distribution, significance testing etc.)

- Basic knowledge of machine learning techniques like Regression, Classification etc.

- Strong business acumen combined with a curiosity to tackle complex problems and drive tangible impact.

What do we expect from you?

- Creative and structured thinking to solve real-world problems

- Fail fast, learn faster approach

- Comfortable in a high-energy, fast-paced environment

- Proficient verbal and written communication skills

- Detail-oriented with the ability to self-direct work in an unstructured

environment

- Excellent partnership and collaboration skills with the ability to work

cross-functionally

- Good organizational skills including prioritizing, scheduling, time

management, and meeting deadlines?

What will you work on ?

- Analyze large, complex data sets to address business challenges, using advanced analytical techniques when required.

- Translate these analysed data insights into compelling narratives aligned with organizational strategic priorities.

- Regularly monitor, forecast, and report on key business metrics.

- Lead planning cycles and performance reviews to drive continuous improvement and adapt to change.

- Define and track the right metrics to measure progress against business goals.

- Design, execute, and evaluate experiments to validate business hypotheses.

- Accelerate root cause analysis and insight generation by building automation and self-serve analytics solutions.

- Collaborate with Business, Product, and Data Engineering teams to enhance data accuracy through improved instrumentation, feedback loops, and process refinements.

- Manage stakeholders effectively by aligning on priorities, communicating insights clearly, and driving data-backed decision-making.