Data Scientist

Econometrica

$110K — $130K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in designing and maintaining AI systems and predictive models.
  • 5+ years of building analytic rules using advanced tools.
  • 5+ years in developing regression and classification models.
  • 3+ years of data support in financial fraud investigations.
  • 3+ years of experience in data manipulation with Python and Pandas.
  • 3+ years working in modern cloud environments (Azure, AWS, GCP).
  • 2+ years in SQL database analysis and developing NLP solutions.

Responsibilities

  • Design and maintain AI systems for fraud detection.
  • Develop regression, classification, and anomaly detection models.
  • Analyze data quality from source tables and develop repeatable processes.
  • Collaborate with criminal investigators on analytical strategies.
  • Integrate NLP techniques to analyze unstructured text data.
  • Manipulate data for machine learning workflows using Python.
  • Create visualizations and dashboards to communicate model outcomes.

Benefits

  • Being part of a dynamic and growing research group.
  • Company-sponsored health plan with optional dental/vision.
  • Excellent opportunities for training and professional development.
  • Referral bonuses for bringing in new talent.
  • 401(k) program for retirement savings.
  • Organized social activities to foster team bonding.
  • Metro SmartBenefits® Program for commuting support.
Full Job Description
Job Title

Data Scientist

Job Type

Full-time

Location

Bethesda Office - Bethesda, MD 20814 US (Primary)
Remote (Virtual) - US - US

Travel

Job Description

The Opportunity

Econometrica is seeking an experienced Data Scientist to support advanced data analytics services for various Federal agencies. The selected candidate will work alongside a multidisciplinary team of data scientists, data engineers, and stakeholders to design, implement, and maintain fraud identification methods and communicate results to technical and non-technical stakeholders.

Tasks may include the following:

  • Designing, implementing, and maintaining advanced AI systems and predictive models to identify financial fraud, improper payments, or non-compliance.
  • Developing and testing regression, classification, Bayesian, clustering, and ensemble models to identify anomalies, patterns, and predictive variables within large, complex datasets.
  • Performing data quality analysis on source tables to identify abnormalities or inconsistencies and developing repeatable processes for efficiently combining and analyzing large, structured and unstructured data sources.
  • Collaborating closely with criminal investigators to determine and execute analytical strategies supporting fraud investigations, while adhering to federal rules of criminal procedure governing protected information.
  • Integrating and scaling natural language processing (NLP) techniques-including OCR, semantic similarity algorithms, and large language models-to parse, clean, and analyze large corpora of unstructured or semi-structured text.
  • Manipulating and preparing data using Python and Pandas, including aggregating, merging, partitioning, and reshaping datasets in preparation for machine learning workflows.
  • Developing visualizations and dashboards to demonstrate methodological choices, outcomes, and predictive capabilities of machine learning models, and iteratively incorporating end-user feedback.
  • Documenting methodology, test models, and production models in compliance with evidentiary and recordkeeping requirements and preparing plain-language reports and executive summaries for both technical and non-technical audiences.
  • Working within modern cloud environments (Azure, AWS, or GCP) and coordinating with the Data Engineering team to ensure system architecture efficiently supports deployed machine learning models.
  • Creating programming and automation techniques (e.g., using Python, SQL, Power BI, Power Apps, and SharePoint) to improve analytic efficiency and expand the scope of analysis and reporting.

Education and Qualifications

Required Skills and Experience:
  • Five (5) or more years of hands-on experience designing, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised methods.
  • Five (5) or more years of hands-on experience developing analytic rules and models using leading-edge analytic tools and best practices.
  • Five (5) or more years of hands-on experience developing regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
  • Three (3) or more years of hands-on experience providing data support for criminal investigations into financial fraud or abuse of government funds.
  • Three (3) or more years of hands-on experience manipulating data in Python, with required proficiency in Pandas.
  • Three (3) or more years of hands-on experience working in a modern cloud environment (Azure, AWS, or GCP).
  • Two (2) or more years of hands-on experience conducting advanced data analysis in SQL (SQL Server and PostgreSQL).
  • Two (2) or more years of hands-on experience developing and scaling NLP solutions.
  • Two (2) or more years of hands-on experience presenting methods and findings to both technical and non-technical stakeholders, orally and in written products and visualizations.
  • Ability to work effectively in a multidisciplinary team setting and to develop effective relationships with clients, consultants, and contractors.
  • Strong oral and written communication skills.
  • Ability to obtain and maintain public trust security clearance.


Desired Skills and Experience:
  • Experience integrating large language models (LLMs) and generative AI tools into analytics workflows.
  • Experience developing production-grade machine-learning workflows, including model validation, calibration, monitoring, versioning, retraining, and documentation.
  • Experience with Azure Synapse Analytics, Azure Machine Learning, and Azure Data Lake Storage.
  • Certifications in cloud architecture, data science, machine learning, or related disciplines (Azure preferred).
  • Experience creating Power BI dashboards, visualizations, network graphs, interactive maps, or other forms of analytical storytelling.
  • Experience working on projects in a consulting environment, particularly supporting audits, investigations, or federal law enforcement.

Additional requirements for the position could involve occasional travel relevant to the responsibilities noted above.

Education

Master's or doctorate-level degree in data science, machine learning, computer science, mathematics, or a related field; OR ten (10) years of applied work experience in one of the same fields.

Our Generous Benefits Package Includes:
  • Being part of a dynamic research group that continues to grow.
  • Company-sponsored healthcare plan and optional vision/dental coverage.
  • Excellent training and development opportunities.
  • Referral bonuses.
  • 401(k) program.
  • Organized social activities.
  • Metro SmartBenefits® Program.

Work Environment

This position is remote, though candidates may choose to work in Econometrica's office.

The office is located at a Metro stop in beautiful downtown Bethesda, MD, within walking distance of great restaurants and local fare. We have a typical office setting with a quiet to moderate noise level.

Physical Requirements

The physical requirements are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The above job description is not intended to be an all-inclusive list of duties and standards of the position. Other instructions and related duties may be assigned by the employee's supervisor.

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