Senior Data Scientist

Company Description

Integres, LLC is a Service-Disabled Veteran Owned Small Business (SDVOSB) which was established to provide high quality, insightful, agile information technology-based solutions to its customers. Integrity is a foundational element of everything we strive to do. We seek to develop solutions which respond to the evolving challenges that today’s organizations face using our own unique combination of industry best practices, and evolving techniques and technologies. We started Integres with the intent of building "a company with a soul". As such, we take a servant-leadership approach as the long-term strategy for our success. We are cultivating a corporate family culture which demands excellence and accountability while putting a premium on work/life balance. We empower and support our employees to contribute to achieving our corporate goals by interacting with our customers as true partners, rather than treating their engagement as just another job. We seek to be good corporate citizens and encourage and promote employee participation in community and volunteer work.

Job Description

• Position: Senior Data Scientist
• Location: Remote
• Client: Office of the Inspector General (OIG)
• Candidates Required: 2
• Work Authorization: US Citizen

Responsibilities:

• Assist TSD with data analytic products by providing highly skilled and authoritative expertise on analytic methods.
•  Perform data quality analysis on source tables to identify any abnormalities or inconsistencies. 
•  Review, maintain, and provide support using all existing fraud indicators developed by TSD. 
• Develop and refine repeatable processes for efficiently combining and analyzing large data sources (including relational tables, structured and unstructured datasets).
• Collaborate closely with criminal investigators to determine and execute strategies to support cases; proactively address and communicate potential data quality issues and adapt analysis to shifting case needs; adhere closely to federal rules of criminal procedure governing protected information (e.g., Rule 6(e)).
•  Design, develop, and implement advanced statistical and machine learning models targeted at identifying fraud, improper payments, or non-compliance within SBA programs.
• Utilize indicators of potential fraud, improper payments, or non-compliance to develop and test predictive models.
•  Assist in developing case leads for SBA OIG investigations based on model outcomes.
•  Coordinate with the Data Engineering Team to ensure system architecture is designed to efficiently support machine learning models.
• Integrate and scale natural language processing methods to parse, clean, and analyze large corpora of unstructured or semi-structured text data, utilizing OCR, semantic similarity algorithms, and large language models as needed.
• Provide detailed documentation of all methodology, test models, and production models; maintain records in compliance with criminal evidentiary requirements
• Develop visualizations and dashboards to demonstrate methodological choices, outcomes, and predictive capabilities of machine learning models; iteratively solicit and integrate end-user feedback
• Provide outcomes and recommendations in multiple formats, including data summaries and visualizations for investigative staff, and executive summaries for SBA OIG leadership.
• 1Create programming and automation techniques to improve task efficiency using tools such as SharePoint, Python, Microsoft Excel, Power BI, and others.
• Identify new business questions to expand the scope of analysis and reporting.

Qualifications

•  Master's, Ph. D., or doctorate-level equivalent degree in data science, machine learning, computer science, mathematics, or a related field; OR 10 years of applied work experience in the same fields.
• Five (5) or more years of hands-on experience in each of the following:
• Designing, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised models.
• Developing analytic rules and models using leading-edge fraud analytic tools and best practices.
• Developing regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
•  Three (3) or more years of hands-on experience in each of the following:
• Providing data support for criminal investigations into fraud or abuse.
• Manipulating data in Python. (Pandas required.)
• Working in the modern cloud environment (Azure/AWS/GCP). Certifications preferred
• Two (2) or more years of hands-on experience in each of the following:
• Conducting advanced data analysis in SQL (SQL Server and PostgreSQL).
• Developing and scaling NLP solutions.
• Presenting methods and findings to technical and non-technical stakeholders, orally and in written products/visualizations.

The background investigation required for this position is at a sensitivity level of public trust.

Additional Information

Integres offers competitive salaries bolstered by a comprehensive benefits package, which provides safety and security for our employees and their families. Our generous benefits package includes

• Healthcare and Insurance: medical, dental, vision, short- and long-term disability protection, basic life and AD&D insurance
• 401(k) Savings Plan
• Accrued Paid Time Off (PTO)
• Employee Recognition and Rewards
• Employee Referral Bonuses

Integres is an equal opportunity affirmative-action employer.  We encourage Minority/Female/Protected Veteran/Disabled applicants to apply.  Integres, LLC proactively fulfills its role as an equal opportunity employer.  We do not discriminate against any employee or applicant for employment because of race, color, sex, religion, age, sexual orientation, gender identity and expression, national origin, marital status, physical or mental disability, status as a Disabled Veteran, Recently Separated Veteran, Active Duty Wartime, or Campaign Badge Veteran, Armed Forces services Medal, or any other characteristic protected by law.

All your information will be kept confidential according to EEO guidelines.