Data Scientist

LinTech Global•Arlington, VA

44d•$140,000•Onsite

About The Position

Dexian Government Solutions is recruiting for a Data Scientist to support our contract at the USPSOIG in Arlington, Virginia. This role involves working independently and within teams to extract, manipulate, and aggregate data for various projects. The Data Scientist will research, design, and develop visualization solutions, design experiments, test hypotheses, and build scalable models using data science and artificial intelligence methods. They will also design, develop, and adapt mathematical, statistical, and analytical solutions for audit, investigation, research, and support functions. Key responsibilities include leading AI activities such as natural language processing, predictive analytics, and machine learning model development, training, evaluation, testing, refinement, deployment, and maintenance. The role requires translating complex technical findings into understandable narratives, preparing comprehensive documentation, and developing project communications. The Data Scientist will provide advice on data access, quality, and storage, and contribute to training and conference materials. They will perform comprehensive data collection and analysis, identify and develop information sources from structured and unstructured data, and interpret data as actionable intelligence to detect, prevent, and respond to fraud, waste, and abuse. The position involves using relational databases, data lakes, and data lakehouses to create analytic products, interacting with other agencies to share information, and developing substantial knowledge of database applications. Expert proficiency in common data science tools like SQL, Python, R, and JavaScript, as well as knowledge of advanced analytic techniques (machine learning, NLP, AI, text/data mining, statistical methods), business intelligence applications (Power BI, Power Apps), and cloud services (AWS/Azure) is essential. The role also includes coordinating with staff and customers to identify requirements, producing documentation, assisting with programming and visualization solutions, troubleshooting existing projects, and understanding concepts supporting relational databases and data warehousing.

Requirements

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 1 year of experience working with AWS or Azure services such as Databricks, Data Factory, Data Lake, and/or Data Lakehouse technologies.
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.
Experience with Azure DevOps and/or GitHub to support continuous integration and continuous delivery (CI/CD) pipelines and operate within Agile frameworks to iteratively deliver high-quality data products, machine learning models, and artificial intelligence solutions.
Develop, manage, and optimize automated data pipelines to ensure data integrity, support reliable analytics workflows, and enable effective collaboration across cross-functional teams.
Integrate disparate and diverse data sources-including flat files, relational databases, and external systems-using techniques such as JDBC/ODBC connections, REST APIs, and web-scraping methods to support robust analytics and data-driven decision-making.
Experience using PySpark and PySpark SQL to process, transform, and analyze large-scale datasets.
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).
This role requires customer approval, suitability to hold a public trust and successful completion of a preemployment background screening.

Responsibilities

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 OIG 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 JavaScripts), 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.
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.
Experience with Azure DevOps and/or GitHub to support continuous integration and continuous delivery (CI/CD) pipelines and operate within Agile frameworks to iteratively deliver high-quality data products, machine learning models, and artificial intelligence solutions.
Develop, manage, and optimize automated data pipelines to ensure data integrity, support reliable analytics workflows, and enable effective collaboration across cross-functional teams.
Integrate disparate and diverse data sources-including flat files, relational databases, and external systems-using techniques such as JDBC/ODBC connections, REST APIs, and web-scraping methods to support robust analytics and data-driven decision-making.
Experience using PySpark and PySpark SQL to process, transform, and analyze large-scale datasets.
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).