Lead Data Scientist | Remote

The Data Science Department has an opening for a Lead Data Scientist. This position is located in Pleasanton, California.

Position Purpose
Client s Data Science team is looking for an experienced Data Scientist to work for the most transformational food and drug retailers in the United States.

Data Science at client end is inspired to build best in class customer experience and revolutionize the food and drug retail industry. We are looking for people who are excited in re-imagining the grocery experience by harnessing the power of AI and digital technologies. The Data Science team collect and rely on big data from existing stores and customer interactions at the 2300 nationwide stores and beyond. We are a highly driven team that apply data science to delight our customers, to improve store operations, to optimize supply chain and to proactively improve product lifecycle.

You will enjoy working with one of the richest data sets in the world, cutting edge technology, and the ability to see your insights turned into business impacts on regular basis. You'll work closely with other data scientists and business partners in identifying and defining data science projects, building machine learning algorithms and models on top of existing data platforms. The candidate will have a background in computer science or a related technical field with experiences working with large data sets and applying data-driven decision making. A successful candidate will be both technically strong and business savvy, with a passion to make an impact through creative storytelling and timely actions. You are a self-starter, smart yet humble, with a bias for action.

Key Responsibilities include, but are not limited to:

• 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 generate customer behavior segmentation, to build recommendation engines and deliver personalized user experience on ecommerce website and loyalty mobile app
• 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 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 feedbacks using Natural Language Processing. Develop adaptable NLP solutions including text categorization, domain classification, event detection, and topic modeling
• 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 sophisticated machine learning and modeling solutions with intuitive visualizations and effective communications

• Masters or PhD degree in quantitative discipline: Computer Science, Engineering, Data Science, Math, Statistics or related fields
• 7+ 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.
• 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 Snowflake, 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