Senior Data Scientist

Job Title: Senior Data Scientist

Location: Hybrid position 2x/week in Vienna, Virginia

Duration: 6+ months

Responsibilities:

• Lead end-to-end data science projects, delivering innovative, data-driven solutions that address complex business challenges and drive measurable outcomes.
• Design, develop, and validate advanced machine learning and statistical models, ensuring optimal performance and scalability.
• Collaborate closely with machine learning engineers to deploy models in production environments, both real-time and batch, while implementing performance monitoring and improvement strategies.
• Partner with key business stakeholders to translate strategic goals into actionable data science opportunities and provide insights that inform decision-making.
• Build and maintain strong cross-functional relationships, fostering deep collaboration with product, engineering, and business teams.
• Serve as a subject matter expert in machine learning and predictive analytics, providing guidance on best practices and model interpretability.
• Stay current with emerging trends, research, and advancements in data science, continually exploring new methodologies and technologies to enhance solution effectiveness.

Required Skills & Qualifications:

• 12+ years of progressive experience in Data Science, Machine Learning, and Artificial Intelligence with a strong record of driving enterprise-level AI initiatives.
• Proven expertise as a Machine Learning & Artificial Intelligence Expert / SME, leading end-to-end solution architecture, model development, and deployment.
• Deep hands-on experience with Databricks (Lakehouse architecture, Delta Lake, MLflow, Unity Catalog) recognized for SME-level proficiency.
• Advanced programming skills in Python, PySpark, and SQL for large-scale data engineering and model development.
• Strong experience in building, training, and operationalizing ML/AI models across Azure, AWS, and Google Cloud Platform cloud platforms.
• Comprehensive understanding of machine learning algorithms, deep learning architectures, and NLP techniques.
• Skilled in MLOps, including Feature Store management, MLflow tracking, and Model Serving for scalable and governed AI deployment.
• Domain expertise in Supply Chain Analytics, including demand forecasting, inventory optimization, and logistics modeling.
• Excellent leadership, communication, and stakeholder management skills with a proven ability to bridge technical and business teams effectively.