Data Scientist eCommerce
Quick Overview
Job Description
Data Scientist
6- 12 months - St. Louis, MO
This is day 1 onsite.
Role Description - Our customer s Digital and eCommerce division is looking to transform the Digital and eCommerce technology engine. As a Data Scientist eCommerce Search, you will play pivotal role in building the next generation of intelligent, high-performing search experiences for our global eCommerce platforms and build new features and components in our evolving platform, helping to embrace with search metrics, dashboards, model fine tuning.
ESSENTIAL JOB FUNCTIONS
* Machine Learning Model Development: Design, train, and evaluate ranking models (learning-to-rank, neural networks, embedding-based approaches) to optimize search relevance and personalization.
* Search Query Analysis: Analyze search query logs, evaluate user behavior data to identify opportunities for relevance improvements and inform ranking strategies.
* Feature Engineering: Develop and engineer features from search, product, and user data to power ML models and improve ranking performance.
* Semantic Search & NLP: Implement semantic search for improved product discovery across chemistry and life science domains.
* Search Engine Tuning: Optimize Elasticsearch/Lucene configurations, including tokenization, stemming, query parsing, and lexical search algorithms (BM25) to work in concert with ML models.
* ML Pipeline Development: Build and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment using MLOps best practices.
* Ranking & Personalization: Develop personalized ranking strategies that adapt to user segments, query intent, and business objectives; integrate collaborative filtering and content-based approaches.
* Performance Monitoring & Iteration: Monitor search and ML model performance metrics in production; identify drift and continuously improve models based on new data and domain insights.
* Data Analysis
QUALIFICATIONS Education- Bachelor s degree in Computer Science, Engineering, Data Science, or a related quantitative field.? ?
Mandatory Skills:
*5 years of hands-on experience in machine learning, data science, search relevance, or ranking systems.
* Proven expertise in Python and ML frameworks (MLFlow, TensorFlow, PyTorch, Scikit-learn, or equivalent).
* Strong background in statistical analysis, data exploration, and working with large-scale datasets.
* Experience with feature engineering, data preprocessing, and data manipulation libraries (Pandas, NumPy, Spark).
* Demonstrated experience building or working with ranking models (learning- to-rank, neural ranking, or similar).
* Experience with semantic search, embedding, or dense retrieval methods.
* Deep understanding of search engines (Elasticsearch, Solr, OpenSearch), lexical search algorithms (BM25), information retrieval concepts, search relevance tuning, tokenization, stemming, and query parsing.
* Experience with MLOps practices and tools (model versioning, experiment tracking, pipeline orchestration).
* Proficiency in SQL and querying large datasets.
* Strong problem-solving and analytical skills with the ability to think critically about complex search and ranking problems.
* Excellent communication skills; ability to explain ML and search concepts to both technical and non-technical stakeholders.
* Ability to collaborate with cross-functional teams
Skills
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