Senior Data Scientist - 26-00551

Job Description LeadStack Inc. is an award winning, one of the nation's fastest growing, certified minority owned (MBE) staffing services provider of contingent workforce. As a recognized industry leader in contingent workforce solutions and Certified as a Great Place to Work, we're proud to partner with some of the most admired Fortune 500 brands in the world. Job Title: Senior Data Scientist, Recommender Systems (Relevancy / Personalization & Loyalty Strategy) Location: Cincinnati, OH, Onsite Duration: 12+ months Pay Rate: $70/hr – $90/hr (W2) Role overview: The Relevancy/Personalization team builds large-scale personalized customer experiences for a major e-commerce site, delivering recommendations at scale to millions of customers. The team covers product and coupon recommender systems, substitute recommendations, and shoppable recipes. We seek a talented and experienced senior data scientist specialized in building search and recommender systems, with a track record developing deep learning models, expertise in ML frameworks, and strong understanding of recommendation techniques. Responsibilities: • Design, develop, and implement recommender systems tailored to retail and e-commerce personalization needs. • Build advanced machine learning and deep learning models for personalized product, coupon, substitute, and recipe recommendations. • Define evaluation methods and key metrics to measure recommender performance and identify improvements. • Conduct A/B testing and offline model evaluations to compare recommendation strategies. • Perform root cause analysis and model interpretability reviews to understand and improve results. • Improve personalization by incorporating customer preferences, dietary needs, shopping behaviors, and engagement signals. • Explore recommendation diversity strategies to expose customers to a broader range of relevant products while maintaining accuracy. • Partner with ML engineers to support model deployment, serving, versioning, and production pipeline best practices. • Collaborate with data scientists, data engineers, full-stack engineers, product teams, and business stakeholders. • Integrate transactional, customer, product, demographic, and user feedback data for model development and analytics. • Build customer analytics pipelines, reporting dashboards, and performance tracking to monitor recommendation effectiveness. • Document best practices, technical insights, lessons learned, and contribute to internal tools and libraries. • Participate in knowledge-sharing sessions and technical discussions. Required skills / Must-have qualifications: • 2+ years proven experience building deep learning models for large-scale recommender systems. • Recommender systems/personalization experience is required. • Partnering or familiarity on model deployment & MLOps should be sufficient. • Azure/Databricks/Spark is strongly preferred, but demonstrated experience with GCP is acceptable. • Proficiency with ML frameworks such as TensorFlow or PyTorch. • Proficiency in SQL, Python, and Spark for data analysis and manipulation. • Strong statistics, design of experiments, exploratory data analysis, and insights generation. • Experience with cloud platforms (Azure or GCP). • Experience collaborating with Data Engineering and MLOps for model deployment. • Strong problem-solving, analytical, and communication skills; ability to convey complex ideas to technical and non-technical stakeholders. know more about current opportunities at LeadStack , please visit us on https://leadstackinc.com/careers/ Should you have any questions, feel free to call me on (513) 3184502 or send an email on waseem.ahmad@leadstackinc.com