- Primary responsibilities will include working closely with the Estimations, Data Operations, and Engineering teams.
- This will include helping and assist our clients on large datasets; focused on data projections, estimations, and validation.
- Work with Estimations & Methods and Data Operations teams to ensure data delivered to clients is of high quality and ready for analysis
- Lead monthly data refresh validations, leveraging automation tools and working closely with the Data Operations team to refine process over time
- Assist with research of secondary information to validate data trends
- Assist in implementation of data science methods such as forecasting, regression, anomaly detection, clustering, and other machine learning techniques as part of estimations toolkit where appropriate
- Help team in improving quality of core data assets as well as enhance analytic capabilities of delivered data
- Research, suggest and implement best practices for management of market measurment data, projections,



and analytics from Pyxis vast array of alternative data sources and supplemental datasets
- Contribute to internal and external applications by developing analytical services that enable scalable data processes and democratize data techniques across team members
- Prepare various sources of data using data wrangling methods in Python, R and SQL, leveraging infrastructure including Cloud computing solutions and relational database enviroments
- Assist with creation and documentation of standard operating procedures for repeated data processes, as well as knowledge base of data methods

About you
- 3+ years of experience in data mining, statistical modelling, and data analysis, preferably in ecommerce industry, with at least bachelors in mathematics, engineering, science, statistics or technical degree
- Expertise working with large data sets and proficiency in SQL, Excel
- Experience in Python
- Experience in statistical analysis and A/B testing, predictive modeling

📌 Associate - Data Ops Estimations (Data Business CoE) (Delhi)
🏢 Bain Company India
📍 Delhi