Raas Infotek LLC
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.
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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.
#J-18808-Ljbffr