Senior Data Scientist (Public Trust)

Position Overview

As a Senior Data Scientist, you will design, implement, and maintain advanced fraud identification models and communicate analytical results to critical stakeholders. You will collaborate closely with criminal investigators to develop targeted predictive models, integrate natural language processing (NLP) into workflows, and establish repeatable analytical methods for massive datasets.

Key Responsibilities

• Model Development: Design, test, and deploy supervised and unsupervised machine learning models (regression, Bayesian, clustering, ensemble algorithms) to detect fraud, improper payments, or non-compliance.

• Investigative Collaboration: Partner directly with criminal investigators to execute strategies supporting active cases, adapt analyses to shifting needs, and adhere to federal rules governing protected information (e.g., Rule 6(e)).

• Text & NLP Analytics: Scale NLP methods to parse, clean, and analyze unstructured text data using OCR, semantic similarity, and Large Language Models (LLMs).

• Data Quality & Visualization: Perform data cleaning and quality analysis on source tables. Create dashboards and visualizations (via Power BI, Python, etc.) to present methodology and findings to technical and executive leadership.

• Compliance Documentation: Maintain thorough records and detailed methodology documentation compliant with criminal evidentiary requirements.

Required Qualifications

• Education: 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 these fields.

• Hands-on Experience:

  • Designing, implementing, and maintaining advanced AI systems and predictive models (supervised/unsupervised).

  • Developing analytic rules and models using leading-edge fraud analytics tools and best practices.

  • Developing regression, classification, and statistical models to identify anomalies, patterns, and predictive variables.

• Hands-on Experience:

  • Providing data support for criminal investigations into fraud or abuse.

  • Making manipulations in Python utilizing Pandas (required).

  • Working in modern cloud environments (Azure preferred, AWS, or GCP; certifications a plus).

• Hands-on Experience:

  • Advanced SQL data analysis (specifically SQL Server and PostgreSQL).

  • Developing and scaling NLP solutions.

  • Presenting technical methods and findings orally and via written products/visualizations to diverse stakeholders.

Projected Compensation Range

The projected compensation range for this position is $120,000.00 to $165,000.00 (annualized USD).

What We're Looking For

We're looking for technically curious data scientists who enjoy exploring emerging technologies and applying them to real-world investigative challenges. Whether your expertise lies in machine learning, large language models, graph analytics, relationship discovery, or advanced AI techniques, you'll help build innovative analytical capabilities that strengthen government oversight, accelerate fraud detection, and support investigators in protecting the integrity of federal programs.

What you can expect from us

• Real opportunity for career growth in an environment where your achievements will be celebrated

• Constant collaboration with numerous teams to ensure client success

• A team that respects and embraces your ideas and expertise

• Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain

• A workplace dedicated to supporting and bettering public safety and government agencies

Benefits

• Competitive salary based on qualifications and experience

• Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)

• 401(k) with company match

• Travel & performance incentives

• 3 weeks paid time off (plus Federal Holidays)

• $5K annual training allowance

• $500 book allowance

• Tuition reimbursement program

Equal Employment Opportunity

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.