Data Scientist

We are seeking a pragmatic, results-oriented Data Scientist focused on Applied AI & ML to design, develop, and deploy production-ready machine learning and LLM-powered solutions. The role combines strong ML engineering, LLM and RAG experience, data platform know-how (lakehouse, Azure, Fabric), and business intelligence skills to support analytic products, data-driven decisions, and agent/AI quality. You will partner with cross-functional teams to translate business problems into scalable AI solutions, implement retrieval-augmented generation (RAG) systems, and maintain data pipelines and monitoring for model performance and reliability., * Design, develop, and deploy machine learning models and LLM-based solutions (including retrieval-augmented generation) to solve business problems and automate decision processes.

• Build and maintain data pipelines and lakehouse integrations on Azure and Microsoft Fabric to ensure reliable data access for training, inference, and BI reporting.
• Implement, evaluate, and optimize LLMs and prompt engineering techniques for production use, including fine-tuning, retrieval strategies, and hybrid retrieval-indexing architectures.
• Collaborate with engineering, product, and analytics teams to define requirements, deliver prototypes, production models, and end-to-end solutions that provide measurable business value.
• Develop tooling and processes for model governance, versioning, monitoring, A/B testing, and agent quality assessment to ensure robust, safe, and auditable AI systems.
• Create and maintain SQL queries, Python scripts, and ETL processes to support feature engineering, training data preparation, and operational inference workloads.
• Deliver BI dashboards and reports (Power BI) and provide data support to stakeholders, translating model outputs into actionable insights and recommendations.
• Optimize model performance and cost across cloud infrastructure, including compute, storage, and inference pipelines on Azure.
• Document solutions, best practices, and runbooks; mentor junior team members and contribute to continuous improvement of AI/ML practices.

Do you have experience in Unsupervised learning?, Do you have a Master's degree?, * Bachelors or Masters degree in Computer Science, Data Science, Statistics, Engineering, or a related field; PhD preferred but not required.

• 3+ years experience in applied machine learning, data science, or ML engineering, with a track record of delivering production ML or AI solutions.
• Hands-on experience with large language models (LLMs), prompt engineering, fine-tuning, and building retrieval-augmented generation (RAG) systems.
• Strong programming skills in Python and experience writing performant SQL for feature extraction and analysis.
• Experience with cloud platforms preferably Azure and familiarity with Microsoft Fabric, lakehouse architectures, and cloud-native data services.
• Proficiency in BI tools, particularly Power BI, to build dashboards and communicate analytical insights to business stakeholders.
• Experience with model monitoring, A/B testing, model governance, and agent quality evaluation for conversational agents or automated decision systems.
• Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, feature engineering) and MLOps practices.
• Excellent communication skills and ability to work cross-functionally to translate business needs into technical solutions.
• Preferred: experience with additional tools and libraries for LLM deployment (e.g., LangChain, Hugging Face, Azure OpenAI), and familiarity with containerization and CI/CD for ML workflows.

Pulled from the full job description

• 401(k)
• Health insurance
• Paid time off
• Vision insurance
• Dental insurance
• Profit sharing
• On-site gym, * Health
• Dental
• Vision
• 401(k)
• Profit Sharing
• On-Site Fitness Center
• PTO + Floating Holidays