• Design, develop, and deploy machine learning and data science solutions using Python. • Build and maintain reusable Python libraries and analytical frameworks. • Develop machine learning models, data visualization solutions, and analytical dashboards. • Build and deploy APIs and cloud-based applications. • Implement and maintain CI/CD pipelines for machine learning workflows. • Deploy, monitor, and optimize machine learning models on Microsoft Azure. • Collaborate with business stakeholders to translate business requirements into technical solutions. • Maintain technical documentation and follow software engineering best practices. • Stay up to date with emerging technologies and industry trends relevant to the role.

• Serve as a technical lead on AI and machine learning initiatives, providing guidance on solution architecture, model selection, implementation approaches, and technical best practices. • Mentor and support junior and mid-level data scientists through code reviews, knowledge sharing, technical coaching, and collaborative problem solving. • Establish and promote best practices for MLOps, model evaluation, model monitoring, reproducibility, and responsible AI development • Build and deploy end-to-end ML pipelines on AWS (e.g., SageMaker, S3, Glue) for scalable training, evaluation, and inference. • Develop and implement advanced NLP solutions, including text classification, entity recognition, topic modeling, and semantic search using models such as BERT and transformer-based architectures. • Design, build, and productionize RAG (Retrieval-Augmented Generation) systems, including document ingestion, embedding pipelines, vector search, and LLM orchestration. • Develop LLM-powered applications, including prompt engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost. • Contribute to agentic AI system design, including multi-step reasoning workflows, tool use, and orchestration of LLM-driven agents for complex tasks. • Implement predictive analytics and statistical modeling to uncover patterns, trends, and insights from healthcare data. • Evaluate emerging AI technologies, frameworks, and techniques and recommend their appropriate application to government healthcare use cases. • Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets. • Contribute to technical leadership across multiple AI initiatives while remaining an active hands-on developer and model builder. • Build data visualizations, dashboards, and analytical tools to communicate findings clearly to technical and non-technical stakeholders. • Evaluate model performance using appropriate metrics (e.g., accuracy, AUC, precision/recall) and present results in a clear, actionable manner. • Collaborate in an Agile environment with cross-functional teams including engineers, analysts, and stakeholders. • Recommend data-driven solutions and AI strategies aligned with CMS business needs and healthcare policy objectives.

• Drive the end-to-end development of battery state estimation algorithms, such as State of Energy/Charge/Power/Health. • Utilize a deep understanding of BESS, from individual cell level physics to system level topology and state estimation metrics. • Design, build, and deploy AI/ML State estimation models for predicting energy availability, critical for optimal BESS trading strategies. • Work closely with cross-functional teams, including product, energy market analysts, engineering, and DevOps, to define requirements, integrate models into production pipelines, and deliver scalable, cloud-integrated data products. • Stay abreast of state-of-the-art AI/ML and deep learning techniques published in literature. • Lead the transition of AI/ML models from research to production, ensuring robust, scalable, and efficient software development practices. • Leverage expertise in efficiently handling large-scale, noisy battery data. • Serve as a technical resource and mentor for junior team members, contributing to the strategic technical roadmap for the AI/Data Science team.

Title: Data Scientist- 3614880 Location: Arlington, Virginia, United States Salary/Payrate: $125K-$130K annually W2 Work Environment: Hybrid (#1 of days WFH) Term: Contract (12+ months) with possible opportunity of conversion Bachelor’s degree required: Yes Referral Fee: AMS will pay $500 should the person you refer gets hired hybrid Job Description: Our federal client is looking to hire a Data Scientist at their offices in Arlington, VA. This is a long-term (12 months, renewable) contract that allows for one day a week remote work. Please send your resume in WORD format should you be interested in exploring this role. The position is on a contract to hire basis and will pay an annual salary of $125K to $130K (dependent on experience) on a W2 basis with full benefits and PTO. ***Due to the required clearance with our government client, only US Citizens may be considered. Clearance requires that the candidates have resided in the US for the past five years. The selected candidate cannot have left the country for longer than 90 consecutive days and no more than 180 cumulative days*** Position Description - Works independently and within teams to use the necessary data extraction, manipulation, and aggregation techniques to prepare, clean, normalize, and validate data to complete varied projects and tasks. - Researches, designs, and develops visualization solutions using a range of methods which support investigative and audit products. - Designs experiments, tests hypotheses, and builds scalable models using data science and artificial intelligence (e.g. machine learning) methods. - Designs, develops, and adapts mathematical, statistical, econometric, and other analytical solutions for audit, investigation, research, and support functions. - Leads artificial intelligence activities such as natural language processing, predictive analytics, and machine learning model development, training, evaluation, testing, refinement, deployment, and - maintenance. - Translates complex technical findings into an easily understood narrative. Prepares comprehensive documentation for requirements, test plans, user manuals, technical diagrams, and training materials. - Develops project communications and maintains effective working relationships between project teams, stakeholders, and management. - Provides advice on issues affecting projects, such as data access, quality, storage, and other related needs. - Contributes to and presents training and conference materials to large audiences. - Independently performs comprehensive and efficient data collection and analysis of a variety of data sources to develop trends, descriptive statistics, or other insights. - Uses expert level knowledge to identify and develop sources of information from structured and unstructured data, criminal intelligence databases, public information sources, internal Postal Service databases, reference manuals, and audit and law enforcement reports. - Independently researches, extracts, evaluates, interprets, and visualizes data and information as actionable intelligence for auditors and investigators to detect, prevent, and respond to fraud, waste, and abuse. - Uses relational databases, data lakes, data lakehouses, and other data environments to create a variety of analytic products such as business intelligence tools, summary tables, comparison graphs, or temporal, association, and link analysis charts. - Interacts with other agencies and builds relationships with peers to share information and learn the latest developments in analytical tools and techniques to effectively support the client’s with mission related work. - Develops substantial knowledge of database applications and environments and shares expertise with coworkers in support of agency goals and objectives. - Expert proficiency in common data science tools, including scripted languages (such as SQL, Python, R, and Java Scripts), Integrated Development Environment and analytics platforms, open-source solutions, commercial off-the- shelf tools and hardware-based capabilities to support the data analytic development process and creating models, dashboards, and reports. - Knowledge and experience using advanced analytic techniques such as machine learning, natural language processing, robotics process automation, artificial intelligence, text and/or data mining, and statistical and mathematical methods. - Knowledge and experience using business intelligence applications and reporting technologies/methodologies including Data Analytics Expressions (DAX), data Mash-up(M), and Microsoft Power Platform (e.g., Power BI, Power Apps, Power Automate, etc.). - Knowledge of AWS or Azure Services, including Databricks, Data Factory, Data Lakehouses, and Data Lake. - Knowledge of Extraction, Transformation, and Load (ETL) strategies, pattern recognition, and application of analytical tools. - Coordinate with staff and customers to identify business and technical requirements. - Produce written documentation and artifacts for all work completed, including the translation of user requirements into technical designs. - Assist the agency in the development of programming and visualization solutions. - Troubleshoot and provide support on existing projects or application efforts. - Understand the concepts supporting relational databases, data warehousing, data governance, data access, data quality and related areas. - Knowledge of ODBC connection strings, and other external data source connection protocols. - Engineer data analytic solutions, including prototyping, proof of concept, and full implementation. - Evaluate, assess, document, and test data security and continuity of operations for systems and programs. - Ensure compatibility between equipment and software, analyze operational/systems requirements, support design reviews, and present technical briefings. Position Requirements - Proficiency in common data science tools and programming and scripting languages such as SQL, Python, R, and JavaScript with a proven ability to create solutions in complex environments, including the use of programming languages to create datasets, visualizations, and interactive reports in various business intelligence applications. - Skill applying analytical techniques, methods, and processes to business problems demonstrated through a history of accepted modeling and analyses that resulted in meaningful business impact. These include working with unstructured or structured data and converting those data sets using a variety of analyses such as optimization, simulation, classical and spatial statistics, and/or programming languages. - Skill using advanced analytic techniques such as machine learning, natural language processing, robotics process automation, artificial intelligence, text and/or data mining, and statistical and mathematical methods. - Strong writing and documentation skills to capture collection of source data, methodology from business rules, and visualization deployment from a myriad of sources and interactions with various stakeholders. - Perform analysis of data for Extraction, Transformation, and Load (ETL) strategies, pattern recognition, and application of analytical tools. - Review, analyze, and modify existing products including coding, debugging, testing, and documenting. - Provide guidance to coworkers on business and technical issues affecting projects, such as data access, data quality, storage capacity, and analytic tools and software. - Assist with training and conference development which may include presentations to large audiences. - Facilitate between business owners and end-users who need to communicate with database administrators and traditional IT support staff. - Ensure that quality/security guidelines are followed. - Strong relational database and querying languages experience. - Strong verbal and written communication skills. - Must be able to work effectively in a team environment. - Understand and follow a software development lifecycle (analysis, design, development, coding, testing, debugging, and documenting). Desired Requirements - Specialized experience working with programming languages (e.g., Python), business intelligence tools (e.g., Power BI), and analytics platforms (e.g., Databricks). - Knowledge and experience in the law enforcement and/or audit industry - Knowledge and experience using cloud computing platforms such as Azure - Knowledge and experience with relational databases and structured query language (SQL) Experience - Degree in Computer Science, Information Technology, Data Analytics, or related field. - 5+ years’ experience and skill writing coding languages (such as SQL, Python, R, and Java Scripts). - 3+ years’ experience working with projects involving machine learning, natural language processing, robotics process automation, artificial intelligence, text and/or data mining, as well as statistical and mathematical methods. - At least 6 months’ experience working with AWS or Azure services such as Databricks, Data Factory, and Data Lake. Certifications - Professional Certification(s) in a related field of data science and/or data analytics disciplines preferred.