Data Scientist

Roles & responsibilities :

- Collaborate with internal stakeholders and build production grade models and machine learning algorithms on large-scale datasets - Apply machine learning to generate customer behavior segmentation, to enhance recommendation engines and deliver personalized user experience on ecommerce website and loyalty mobile app - Develop Media Mix modelling (MMM), Multi Touch Attribution Model (MTA), Media optimization - Apply predictive modeling techniques and survival models to forecast various demands for operations and to deploy real time learning algorithms to optimize the forecasts - Build data science solutions to fuel growth initiatives for Digital, Merchandising, Marketing and Loyalty teams - Design experiments and deliver A/B Testing analysis to improve customer experience in physical store and on digital platforms - Apply statistical analysis to detect anomaly in systems and outliers in operational metrics for operational excellence - Convey machine learning solutions with intuitive visualizations and effective communications

Experience Required :

- Masters or PhD degree in quantitative discipline: Computer Science, Engineering, Data Science, Math, Statistics or related mathematically-intensive fields such as Experimental Physics or Chemical Engineering - 4+ years of industry experience in applying data science and modeling methodologies: regression model, survival model, ensemble modeling, NLP, recommendation algorithm, clustering, deep learning algorithm, experimental design (Multivariate/A-B testing) and nonparametric Bayesian modeling etc. - Experience with any of the following business analytics practices is preferred: - Marketing-related analytics, including Customer Lifetime Value assessments - Customer Service analytics and advance capabilities including NLP - Personalization and recommendations - Media Mix modelling (MMM). Multi Touch Attribution Modle (MTA), Media optimization, - 4+ years of experience and proficiency in SQL, Python and/or Spark-ML - 4+ years of SQL development skills writing queries, transforming data, mining structured and unstructured data. - 2+ years of hands-on experience in building data science solutions and production-ready systems on big data platforms such as Snowflake, Spark, Hadoop - Ability to write production-level code in Python - Experience with Snowflake, Azure Databricks is a strong plus

Skills Required:

- SQL - Python - Machine Learning - Deep Learning - LLM / Gen AI - Recommendation and personalization Algorithm - Statistical & Mathematical Foundations – Strong knowledge of regression, clustering, survival modeling, and ensemble techniques. - Cross-Functional Collaboration Skills – Ability to work with marketing, media ops, and product teams in a matrix structure.