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Data Scientist

Roles & Responsibilities

  • US Citizen with ability to pass a background check through the VA
  • At least 8 years of experience developing in languages commonly used for data analysis such as Python, R, or SAS
  • At least 2 years of experience developing Reinforcement Learning systems utilizing methods such as Finite Markov Decision Processes, Support Vector Machines, Q-Learning, Stochastic Finite State Machines, MCTS or other hybrid Deep Reinforcement Learning processes
  • At least 2 years of theoretical and practical background in statistical analysis, machine learning, predictive modeling, and/or optimization

Requirements:

  • Leads data science efforts, working closely with clients and data to understand mission and data, and develops and trains AI/ML models
  • Develops, builds, and implements predictive, statistical, or AI/ML models, and refines existing models to improve accuracy and robustness; prepares detailed documentation for models outlining methodology, data sources, assumptions, limitations, and validation results for regulatory and internal review
  • Cleans, transforms, and analyzes large datasets to identify patterns, derive key risk drivers, and prepare structured inputs for model development; conducts testing, benchmarking, and sensitivity analyses to evaluate model performance and ensure compliance
  • Evaluates, recommends, and implements new technologies and updates existing infrastructure to ensure optimal performance; communicates results to both technical and non-technical audiences and works effectively and independently

Job description

Description

 Connected Logistics is seeking a Data Scientist to support the Department of Veteran Affairs (VA) AI Pilot Teams! 


As a Data Scientist you will:

  • Leads data science efforts, working closely with clients and data to understand mission and data.
  • Develops and trains AI/ML models
  • Develop, build, and implement new predictive, statistical, or AI/ML models, and refine existing models to improve their accuracy and robustness.
  • Prepare detailed documentation for models, outlining their methodology, data sources, assumptions, limitations, and validation results for regulatory and internal review.
  • Clean, transform, and analyze large datasets to identify patterns, derive key risk drivers, and prepare structured inputs for model development.
  • Conduct testing, benchmarking, and sensitivity analyses to evaluate model performance, assess model risks, and ensure compliance with internal and regulatory standards.
  • Evaluates, recommends, and executes new technologies and updates existing infrastructure to ensure optimal performance and efficiency.
  • Works in a variety of environments and has excellent verbal and non-verbal communication skills.
  • Works effectively and independently.
Requirements


  • US Citizen with ability to pass a background check through the VA
  • At least 8 years of experience developing in languages commonly used for data analysis such as Python, R, or SAS
  • At least 2 years of experience developing Reinforcement learning systems utilizing at least one of the following methodologies. Finite Markov Decision Processes, Support Vector Machines, Q-Learning, Stochastic Finite State Machines, MCTS or other hybrid Deep Reinforcement Learning processes
  • At least 2 years of theoretical and practical background in statistical analysis, machine learning, predictive modeling, and/or optimization
  • Experience with Jupyter Notebooks, Python, JSON, XML, AI/ML algorithm development
  • Experience with Azure OpenAI, Azure AI Foundry, and/or AWS Bedrock 
  • Experience working with multiple database types such as SQL, Redis and MongoDB
  • Experience building and integrating the at the application and database level
  • Experience developing REST/SOAP APIs and messaging protocols and formats
  • Experience implementing event/data streaming services such as Kafka
  • Experience prototyping front-end visualizations utilizing data visualization suites such as Kibana or Splunk
  • Experience in theoretical and practical background in statistical analysis, machine learning, predictive modeling, and/or optimization.
  • Experience working with large-scale data sets.
  • Experience with the BrownMM DevSecOps toolchain is a plus
  • Experience producing data visualizations for a variety of different audiences.
  • Excellent verbal and written communications skills along with the ability to present technical data and approaches to both technical and non-technical audiences.

 

Total Rewards Statement


We believe in fairness and clarity throughout our hiring process. The anticipated salary range for this position is $140,000.00 to $150,000.00 USD. This is a good-faith range based on factors such as your experience, geographic location, and any applicable contractual requirements, and may vary slightly.


Beyond salary, we provide a robust benefits package and encourage ongoing professional development, because your growth and well-being matter to us. We’re excited to support you in building a rewarding career with us!


Connected Logistics respects the need for confidentiality for all applicants.

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Connected Logistics offers an excellent benefits package that includes health, dental, vision, life, and disability insurance, a great 401(k) package, and generous Paid Time Off.


EOE/Disability/Veterans

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