Senior Data Scientist / Applied Machine Learning Engineer

Job Title: Senior Data Scientist / Applied Machine Learning Engineer

Location: REMOTE

Experience: 8+ Years

Key Skills: Python, Machine Learning Frameworks, Azure Machine Learning, Microsoft Fabric, Azure Data Services, Power BI, Causal Inference

Job Summary

We are seeking an experienced Applied Data Scientist with strong expertise in building predictive machine learning models and performing causal impact analysis using observational data. The ideal candidate will work closely with engineering and business teams to measure the impact of product features and programs on customer outcomes, product health, and revenue using Microsoft Fabric and Azure data platforms.

Key Responsibilities

• Define, build, train, and refine predictive machine learning models using Python and modern ML frameworks.
• Perform causal inference and causal impact analysis on observational data (non-experimental) to evaluate program or feature adoption.
• Design and execute causal models to measure the effectiveness of initiatives such as Telemetry Insights, FastTrack, and product feature rollouts.
• Interpret telemetry data, product health indicators, and business metrics to deliver actionable insights.
• Build scalable, repeatable data science solutions within Microsoft Fabric.
• Collaborate with Fabric and Power BI engineering teams to integrate data science models into dashboards and reporting solutions.
• Leverage Azure Machine Learning and Azure Data Services for model development, deployment, and lifecycle management.
• Communicate analytical findings clearly to both technical and non-technical stakeholders.

Required Qualifications

• 8+ years of experience in Data Science, Applied Machine Learning, or Advanced Analytics.
• Strong proficiency in Python and machine learning libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Hands-on experience with Microsoft Fabric, Azure Machine Learning, and Azure Data Services.
• Proven expertise in causal inference methodologies (e.g., matching, regression, difference-in-differences, synthetic controls).
• Experience working with telemetry data and business metrics in a product or platform environment.
• Strong analytical thinking and problem-solving skills.