
Data Scientist (Remote)
Choctaw Global
Durant, OK 74701
•12 hours ago
•No application
About
YOUR RESPONSIBILITIES:
- 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.
WHAT WE ARE LOOKING FOR:
- At least 8 years of experience developing in languages commonly used for data analysis such as Python, R, or SAS
- 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
- At least 2 years of theoretical and practical background in statistical analysis, machine learning, predictive modeling, and/or optimization
- Experience implementing event/data streaming services such as Kafka
- Experience prototyping front-end visualizations utilizing data visualization suites such as Kibana or Splunk
- 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
- Experience in theoretical and practical background in statistical analysis, machine learning, predictive modeling, and/or optimization.
- Experience developing in languages commonly used for data analysis such as Python, R, Julia, or SAS
- Experience working with databases such as SQL or MongoDB.
- Experience working with large-scale data sets.
- 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.
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