Senior Data Scientist - Relevancy Sciences/Personalization & Loyalty (P3763)

G2 – Senior Data Scientist, Relevancy Sciences, Personalization & Loyalty Strategy

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Relevancy Team is responsible for making relevant and personalized customer experiences for Kroger's e-commerce site, which ranks among the top 10 e-commerce companies in the US. We deliver trillions of recommendations to the Kroger website at scale and make them available to millions of Kroger customers. Scale is the name of the game. The team has a rich portfolio of sciences which include product and coupon recommender systems, substitute recommendations, and shoppable recipes. We apply a multitude of advanced techniques such as deep learning, Matrix factorization, ML, and NLP to create our sciences.

RESPONSIBILITIES:

Technical Leadership

• Build models and solutions using new deep learning architectures and Natural language processing (NLP) methods and algorithms to solve specific problems with search to improve user experience.
• Measure the impact of improving search algorithm, and or other system improvements
• Create benchmark metrics and datasets for evaluating improvements to search algorithms
• Assist with the data collection, feature engineering, model building, develop and validate data annotation strategies
• Lead the value storytelling with dashboards and visualization tools to the Business and Product teams

Identify opportunities

• Identify and validate business use cases that can be solved with AI
• Coordinate with cross-functional teams to seek feedback on models, share results and implement models
• Lead and work with data scientists and ML engineers to adapt and scale NLP solutions
• Develop evaluation strategies for measuring both model performance and real work impact

Measurement and Experimentation – Design, Deploy, Enhance and Measure

• Lead the experimental design and statistical techniques for measurement and experimentation
• Innovate in experimental design and measurement – Bayesian methods, multi-armed bandits
• Partner with Business and Product to identify the right metrics for understanding the customer and product performance
• Partner with Engineering to facilitate experiment deployment and enhancements to experimentation frameworks

Qualifications, Skills and Experience: 

• Bachelor’s or Master’s degree or equivalent in computer science, data science, statistics, mathematics, analytics, or related discipline
• 2+ years of proven track record in ML and NLP
• 2+ years of experience developing analytical solutions using advanced statistical methods, ML algorithms and DL frameworks
• 2+ years of experience with text processing using standard NLP tools (scikit-learn, Spacy) for parsing, entity extraction, POS tagging, topic discovery, classification, natural language understanding (NLU) and working with transformer models
• 2+ years querying data from relational databases using SQL
• 2+ years using Python to develop analytical solutions
• 2+ years with data wrangling, data cleaning and prep, dimensionality reduction using Spark, SQL
• 2+ years with Big Data concepts, tools, cloud solutions and architecture (Azure, GCP, Spark)
• 2+ years of experience using ML frameworks such as Fast.ai, AllenNLP, OpenCV, or HuggingFace
• 2+ years using one of the Deep Learning frameworks such as TensorFlow, PyTorch etc.
• 2+ years of experience in building dashboards and knowledge of visualization tools (Matplotlib, Seaborn, PowerBI etc.)

• Strong understanding of statistics, experimental design, and measurements
• Strong analytical, problem-solving, and decision-making skills
• High level of independence to develop and own toolkits, pipelines, and dashboards.
• Excellent written and verbal communication skills to work with cross-functional teams.
• Ability to work in a highly collaborative environment

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