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.