Senior Data Scientist

As a leading food and drug retailer in the United States, Albertsons Companies, Inc. operates over 2,200 stores across 35 states and the District of Columbia. We build and shape technology solutions that solve customers’ problems every day, making things easier for them when they shop with us online or in a store. We have made bold, strategic moves to migrate and modernize our core foundational capabilities, positioning ourselves as the first fully cloud-based grocery tech company in the industry. Our success is built on a one-team approach, driven by the desire to understand and enhance the customer experience. By constantly pushing the boundaries of retail, we are transforming shopping into an experience that is easy, efficient, fun and engaging. At Albertsons Companies India, we're not just pushing the boundaries of technology and retail innovation, we're cultivating a space where ideas flourish and careers thrive. workforce and important to the next phase in the company’s technology journey to support millions of customers’ lives every day. At the Albertsons Companies India, we are raising the bar to grow across Technology & Engineering, AI, Digital and other company functions, and transform a 165-year-old American retailer. At Albertsons Companies India associates collaborate directly with international teams, enhancing decision-making processes and organizational agility through exciting and pivotal projects. Your work will make history and help millions of lives each day come together around the joys of food and inspire their well-being. Position Title: Senior Data Scientist Big part of your responsibilities will be project-based. You will be responsible for identifying and providing solutions and tooling built on predictive modeling, machine learning algorithms that satisfy various business needs Use machine learning algorithms to create Media Mix modelling (MMM). Multi Touch Attribution Model (MTA), Media optimization, dynamic pricing and dynamic bid optimization, Click Through Rate prediction, Forecast Display product Ads & Sponsored Ad inventory Use machine learning algorithms to generate customer behavior segmentation, measure campaign effectiveness by tracking campaign success KPIs Build data science solutions to solve complex problems and fuel growth initiatives for Digital, Merchandising, Marketing and Loyalty teams Extract insights and scale sentiment analysis from comments and other forms of feedback using Natural Language Processing. Design experiments and deliver A/B Testing analysis to improve customer experience in physical stores and on digital platforms Apply statistical analysis to detect anomaly in systems and outliers in operational metrics for operational excellence Convey sophisticated machine learning and modeling solutions with intuitive visualizations and effective communication Experience Required: ~ Bachelor's or Master's or PhD degree in quantitative discipline: Computer Science, Engineering, Data Science, Math, Statistics or related fields ~5+ 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. ~ Business experience and familiarity with Retail industry-related Data Science capabilities including forecasting, optimization, categorization, recommendations, time-series models, deep learning and predictive analytics is preferred ~5+ years of experience and proficiency in Python and/or Spark-ML ~5+ years of SQL development skills writing complex queries, transforming data, mining structured and unstructured data. ~3+ years of hands-on experience in building data science solutions and production-ready systems on big data platforms such as Databricks, Spark, Hadoop ~ Proven track record of leveraging data science solutions to drive impactful business decisions ~ Proven ability to effectively distill and communicate complex machine learning solutions to different audiences ~ Experience with Snowflake, Azure Databricks is a strong plus ~ Experience using data access tools and building dashboards with large datasets from multiple data sources is a plus ~ Building Recommendation/ personalization systems or foundational systems on apps & websites. Experimental design (Multivariate/A-B testing) Python, Spark-ML, SQL, Databricks, Spark, Hadoop, production-level Python coding