About the Role

Lunar Point Systems delivers Microsoft Fabric data solutions for business clients, including predictive modeling and applied machine learning built natively within the Fabric platform. This role owns the full model lifecycle — from KPI definition and feature engineering through training, deployment, and production monitoring — across client engagements that span different industries and problem domains.

Why Us

We believe in creating a supportive, dynamic environment where your skills can truly shine. We offer the opportunity to work on exciting, high-impact projects that push the boundaries of development. Our team is collaborative, innovative, and passionate about delivering exceptional results. If you're looking to make a real impact and be part of a team that values your contributions, Lunar Point Systems is the place for you.

Responsibilities:

• Work with clients and the Lunar Point team to identify business KPIs and define how machine learning can drive measurable progress toward those goals
• Design and run end-to-end ML experiments using Fabric Data Science — including feature engineering, model training, evaluation, and iteration
• Manage experiment tracking and model versioning using MLflow within Fabric Notebooks
• Build reusable feature pipelines stored and governed in OneLake, following medallion architecture conventions
• Deploy trained models into production within the Fabric environment and establish monitoring for drift, accuracy, and performance degradation
• Participate in workspace deployment pipeline promotions (Dev to UAT to Prod) and validate model behavior across environments
• Partner with Data Engineers to produce pipelines and ensure model inputs are reliably delivered at scale
• Communicate model outputs, confidence levels, and business implications clearly to client stakeholders
• Maintain documentation of model architecture, training data, assumptions, and performance benchmarks per client

Requirements:

• Microsoft Certified: DP-600, DP-700, or DP-100
• Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
• 3-5 years of experience in applied data science or machine learning in a production environment
• Strong proficiency in Python (scikit-learn, pandas, NumPy) and SQL
• Hands-on experience with Microsoft Fabric Data Science — Notebooks, MLflow, SynapseML, and Spark-based environments
• Demonstrated ability to connect KPIs to model objectives and explain results to non-technical stakeholders
• Solid foundation in statistics, probability, and core ML algorithms (regression, classification, clustering, ensemble methods)
• Experience with model deployment and post-production monitoring in a cloud environment
• Professional communication skills suitable for client-facing meetings
• Version control experience with GitHub or Azure DevOps (branching strategies, PR workflows, YAML pipelines)
• US citizen; no visa sponsorship available

Nice to Have:

• Master's degree in a related field
• Experience with real-time inference pipelines using Fabric Eventstream or Azure Event Hubs
• Familiarity with Microsoft Purview for data lineage and governance in model training workflows
• Deep learning experience with PyTorch or TensorFlow

Equal Opportunity Employer

Lunar Point Systems is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable federal, state, or local law. All qualified applicants will receive consideration for employment without regard to any such characteristic. We are committed to creating an inclusive environment for all employees and contractors.