Data Scientist

LinTech Global•Arlington, VA

4d•Onsite

About The Position

Dexian Government Solutions is recruiting for a Data Scientist to support our contract at the USPS OIG 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 like machine learning. They will also design, develop, and adapt mathematical, statistical, and econometric solutions for audit, investigation, and research functions. A key responsibility is leading AI activities including 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 and preparing comprehensive documentation. Additionally, the Data Scientist will develop project communications, maintain relationships with stakeholders, advise on data-related issues, and contribute to training and conference materials. They will perform comprehensive data collection and analysis to develop insights, identify and develop information sources from structured and unstructured data, and use various data environments to create analytic products. Collaboration with other agencies and sharing expertise with coworkers are also important aspects of the role. Expert proficiency in common data science tools, scripting languages (SQL, Python, R, JavaScript), IDEs, analytics platforms, and open-source solutions is expected. Knowledge of advanced analytic techniques, business intelligence applications (DAX, M, Power Platform), AWS or Azure Services (Databricks, Data Factory, Data Lake, Data Lakehouse), ETL strategies, pattern recognition, and relational databases is required. The role also involves coordinating with staff and customers, producing documentation, assisting with programming and visualization solutions, troubleshooting, and understanding software development lifecycles.

Requirements

Proficiency in common data science tools and programming and scripting languages such as SQL, Python, R, and JavaScript.
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.
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.
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.
Perform analysis of data for Extraction, Transformation, and Load (ETL) strategies, pattern recognition, and application of analytical tools.
Strong relational database and querying languages experience.
Strong verbal and written communication skills.
Must be able to work effectively in a team environment.
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.
Ability to hold a public trust and successful completion of a preemployment background screening.

Nice To Haves

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.
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.
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.
Experience with 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.).

Responsibilities

Use data extraction, manipulation, and aggregation techniques to prepare, clean, normalize, and validate data.
Research, design, and develop visualization solutions to support investigative and audit products.
Design experiments, test hypotheses, and build scalable models using data science and artificial intelligence methods.
Design, develop, and adapt mathematical, statistical, econometric, and other analytical solutions.
Lead artificial intelligence activities such as natural language processing, predictive analytics, and machine learning model development, training, evaluation, testing, refinement, deployment, and maintenance.
Translate complex technical findings into an easily understood narrative.
Prepare comprehensive documentation for requirements, test plans, user manuals, technical diagrams, and training materials.
Develop project communications and maintain effective working relationships.
Provide advice on issues affecting projects, such as data access, quality, and storage.
Contribute to and present training and conference materials to large audiences.
Perform comprehensive and efficient data collection and analysis of a variety of data sources.
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.
Extract, evaluate, interpret, and visualize data and information as actionable intelligence.
Use relational databases, data lakes, data lakehouses, and other data environments to create analytic products.
Interact with other agencies and build relationships with peers to share information and learn the latest developments in analytical tools and techniques.
Develop substantial knowledge of database applications and environments and share expertise with coworkers.
Coordinate with staff and customers to identify business and technical requirements.
Produce written documentation and artifacts for all work completed.
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.
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.
Develop, manage, and optimize automated data pipelines.
Integrate disparate and diverse data sources using techniques such as JDBC/ODBC connections, REST APIs, and web-scraping methods.
Review, analyze, and modify existing products including coding, debugging, testing, and documenting.
Provide guidance to coworkers on business and technical issues affecting projects.
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.
Understand and follow a software development lifecycle (analysis, design, development, coding, testing, debugging, and documenting).