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Overview
Job Description
Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.
Job Title: Data Scientist- 49417-1 Job Location: Washington, DC
- Position: Data Scientist- 49417-1
- Duration: 12 Months
Additional Skills:
- AWS SageMaker/ AI & ML / Model development / Gen AI development.
Business Justification:
FEP Local systems provides Machine Learning service to FEP Client plans to improve claim processing, provider prediction, and automation that reducing human intervention process. As extension of ML/AI service to other business cases and additional plans joined to this service, we need additional resources to help to development ML program with FEP Local development team.
Responsibility:
- Develop algorithms, write scripts, build predictive analytics, use automation, apply machine learning, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help senior leadership make informed decisions.
- Provide the team with a deep understanding of their data, what it all means, and how they can use it.
- Help with discovering the information hidden in vast amounts of data, and help with making smarter decisions to deliver even better products.
- Applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with products.
- Development new ML model(s) as well as maintaining existing ones and their processes.
- Development Gen AI solution using AI platform like AWS SageMaker, AWS Bedrock, AWS AgentCore.
- Select features, building and optimizing classifiers using machine learning techniques, data mining using state-of-the-art methods, and, enhancing data collection procedures to include information that is relevant for building analytic systems.
- Responsibilities will also include processing, cleansing, and verifying the integrity of data used for analysis and doing ad-hoc analysis and presenting results in a clear manner.
- Creating automated anomaly detection systems and constant tracking of its performance.
Requirements:
- Master's Degree or Ph.D. in STEM with 2 years preferred OR Bachelor’s Degree in STEM with 7 years.
- Experience in predictive modeling, data science, machine learning, or user and entity behavior analytic development.
- Experience in developing predictive, prescriptive, optimization, and forecasting models, including the use of contemporary techniques such as and not limited to support vector machines, neural networks, and gradient boosting.
- Experience in developing of Generative AI solution with LLM and custom model to provide AI solution to business.
- Experience in interpreting results from statistical and mathematical models.
- A minimum of two years’ experience in applying Data Science/ Analytics to Health Insurance/Health Care related problems/use cases.
- At least 1 years focused on applications of Generative AI solution.
- Experience in programming languages like Java, Python and/or R for complex data manipulation, statistical analysis, and machine learning.
- Experience in Analytic development with streaming and a Hadoop ecosystem (Hive, Spark, etc.)
- Experience in SQL, NoSQL, graph-based, Key/Value stores, document stores.
- Experience with cloud base data platform like Snowflake and use training/build model.
- Experience with one or more cloud services (AWS SageMaker, MS Azure)
- Experience applying machine learning to real-world production systems, analytic development based on SparkML and other ML libraries.
- Experience in advanced data visualizations and interpretation using data visualization tools is plus (e.g., Tableau, Power BI).
- Familiarity with common Linux/Unix command line tasks and version control software like git or svn preferable.
- Using and developing statistical analysis, modeling, simulation, and machine learning methods.
- Comfort with complex mathematical concepts and models.
- Experience with Agile Methodology/Scrum Development and DevOps
- History of solving difficult problems using a scientific approach highly preferred
- Ability to communicate and present the work effectively and influence others
- Ability to work in a fast paced environment and shift gears quickly
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