Job Title:- Data Scientist - 2 times a month onsite
Location:- Arlington, Virginia
Duration:- 6+ MO
citizen only
Must PROVIDE ANSWERS TO QUESTIONS
find people with Public trust and say what agency - just any public trust in the past
Contract
the QUESTIONS are at the bottom
We have a permanent position for a Data Scientist in Arlington VA. This role is 2 times a month on site.
Please answer the questions and return for submittal.
Here are the screening questions:
For this role, I'd use questions that force candidates to give specific examples rather than simply confirm they've used Python, SQL, Azure, etc. These five should work well for a first-round recruiter/technical screen:
- Programming & SQL: "Walk me through a recent project where you used Python and SQL to solve a complex data problem. What did you personally build, how complex was the data, and what was the final business outcome?"
- Listen for: 5+ years of hands-on coding, strong SQL/relational database skills, Python proficiency, and clear individual contribution.
- Machine Learning / Advanced Analytics: "Tell me about a production or business-facing project where you applied machine learning, NLP, AI, text/data mining, or another advanced statistical technique. What problem were you solving, what approach did you choose, and how did you evaluate whether it worked?"
- Listen for: 3+ years of substantive advanced analytics experience-not simply exposure to AI/ML tools-and the ability to explain model selection, validation, metrics, and measurable business impact.
- Azure/AWS & Databricks: "Describe something you've built or supported in Azure or AWS. Specifically, what experience do you have with Databricks, Azure Data Factory, Data Lake, or comparable cloud services?"
- Listen for: At least 6 months of genuine hands-on cloud experience. Strong candidates should be able to describe architecture, pipelines, notebooks/jobs, storage, security/access, and their personal responsibilities.
- ETL / Data Engineering & Troubleshooting: "Suppose you're given data from several sources with inconsistent formats, missing values, duplicates, and questionable data quality. How would you design the ETL process and validate the resulting dataset before it was used for analytics or reporting?"
- Listen for: ETL design, data profiling, transformation, SQL/Python, validation/testing, data-quality controls, lineage/documentation, debugging, and awareness of security requirements.
- End-to-End Delivery & Communication: "Give me an example of a data product you took from business requirements through development and deployment. How did you work with business users, IT/database teams, document your methodology, test the solution, and communicate the results to nontechnical stakeholders?"
- Listen for: Full SDLC experience, stakeholder management, documentation, testing/debugging, BI/Power BI experience, teamwork, and the ability to translate between technical and business audiences.
Position Description
Section I: 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.
- Research, designs, and develops visualization solutions using a range of methods that 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 research, 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 scripting languages (such as SQL, Python, R, and JavaScript), 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, robotic 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 Analysis Expressions (DAX), Data Mashup (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
Section II: 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, robotic process automation, artificial intelligence, text and/or data mining, and statistical and mathematical methods.
- Strong writing and documentation skills to capture the 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 communication 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 language 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).
REQUIRED SKILLS/EXPERIENCE:
- 5+ years' experience and skill in writing code in programming languages (such as SQL, Python, R, and JavaScript).
- 3+ years' experience working with projects involving machine learning, natural language processing, robotic 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.
DESIRED SKILLS/EXPERIENCE:
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)
EDUCATION: Degree in Computer Science, Information Technology, Data Analytics, or related field.
| Navya Gupta
Sr. IT Technical Recruiter 
| | | Email: Gtalk:
Phone: +1 Linkedin id:
Address: 505 Knolle Court, Saint Augustine| FL 32092 |
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