Data Scientist

  • Washington DC, DC
  • Full Time
  • Manager/Supervisor

Position Overview

The Company

Censeo Consulting Group is a top Washington D.C. based management consulting firm dedicated to helping public sector and non-profit clients build operational excellence, deliver better outcomes, and lower cost. We take a personalized approach to strategic consulting to solve our clients’ most complex problems and build operational excellence that transforms their organizations, allowing them to better deliver on their public and social missions. 

At Censeo, our award-winning culture means you’ll join a tight-knit community of 50 brilliant and passionate colleagues. We are advocates for a better functioning public sector, and we’re also good friends who know the names of each other’s dogs. Our philosophy is horizontal, not hierarchical, and our open-door policy encourages a culture of entrepreneurship at all levels. We share successes, make decisions together, and foster an environment for those with passion and initiative to lead. Our colleagues bring their own unique personalities to work every day and use them to help shape our growing firm in ways that reach far beyond client projects. 


The Federal Acquisition Service (FAS) Office of Enterprise Strategy Management (OESM), Multiple Award Schedule (MAS) Program Management Office (PMO) has a requirement for a Data Scientist.  The requirements and skills are outlined below; the primary goals of the position are:

  • Identify, clean, and normalize Transactional Data Reporting (TDR) data, Contractor Payment Reporting Module (CPRM) and other data sets for MAS.
  • Build a MAS data model that standardizes the structure and relationships of Sales Reporting Portal (SRP) data with other key data sets across the enterprise that can be used by multiple portfolios.
  • Create business requirements for DX and Contract Acquisition Life-cycle Management (CALM) implementation

Required Qualifications

  • Master of Public Administration (MPA) or Master of Science (MS) degree in Statistics, Mathematics, Computer Science or another quantitative field or a BS/BA degree in these same disciplines AND five years of relevant experience.
  • Proficiency in using Amazon Web Services (AWS), Amazon Simple Storage Service (Amazon S3), Amazon EMR (previously called Amazon Elastic MapReduce), Redshift and Sagemaker
  • High proficiency in PostgresSQL and MongoDB MQL
  • High proficiency using Python or Scala within a Spark environment to manipulate data and draw insights from large data sets.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Collaboration and facilitation skills to work with clients and interdisciplinary teams to comprehend the customer journey, define relevant qualitative and quantitative measurements, uncover actionable insights, and identify opportunities for gaining and retaining clients.
  • Strong problem solving skills with an emphasis on product development and process improvement.

Additional Preferred Experience

  • Ability to make sense of and scale outcomes from qualitative and quantitative data through data analytics, coding and process automation
  • Scale data-driven business outcomes through user feedback, data analytics, coding and process automation of qualitative and quantitative data
  • Work experience in collaborating with developers and communicating with technical team members to implement backlog of product or customer experience improvements
  • Experience with garnering customer and employee feedback for large organizations incorporating industry standards while following federal regulations and policies
  • Demonstrated outcomes and accomplishments for using data and processes to lead new transformation efforts for customer  experience.
  • Be comfortable with unstructured data sets.

Data Scientist Requirements

  • Review and analyze transactional data to determine its usability for Contract Awarded Labor Categories (CALC+) and Price Point Plus Portal (4P).
  • Establish data quality standards and controls for quality assurance
  • Mine and analyze data from databases and quantitative analysis to drive optimization and improvement of product development, marketing techniques, and business strategies.
  • Develop custom data models and enrichment pipelines to apply to data sets.  E.g. employ data algorithms.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques, e.g. Bureau of Labor Statistics (BLS) data.
  • Create and contribute to data intelligence,  measurement, and key metrics. Maintain data evidence standards with user research and unstructured data sets. Be an active contributor to FAS Data Evidence Governance Board activities. .
  • Use algorithms to drive outcomes removing unconscious bias and protecting data ethically.

About The Role and Project

All of the Federal Marketplace (FMP) and Digital Experience (DX) initiatives require extensive data management, analysis and normalization.  FAS has made great strides in the past two years by bringing key data into a FAS Enterprise Data Architecture (EDA) with a data set catalog. In order to bring data into the EDA, data scientists/analysts need to normalize data across multiple systems and sync up data fields to ensure the EDA holds clean, authoritative data that can be used by all of FAS. A good amount of FAS’s data is still held on 30 year old legacy production systems. 

Often, these data sources do not have similar data elements or the field names are not clear for data consumers. More current data sources such as “prices paid” data are reported in inconsistent formats and are in need of data standards.  In order to create unified digital tools for FAS schedule customers, disparate data sources must be painstakingly combined into a unified data structure. Existing data science capabilities within GSA are at or over capacity with demand from across the enterprise.

The outcomes of this process will:

  • Increase data quality
  • Enhances data integrity for the Digital Experience (DX) project
  • Provide faster delivery of quality data to customers in support of unpriced services
  • Support TDR expansion and improve the useability and usage of TDR data

The Fine Print:

  • Expected travel 0-10%; may increase based on business needs
  • This is an exempt, full-time position

Censeo offers a competitive compensation and benefits package, including paid vacation and sick leave, flexible and remote work opportunities, and tuition and training reimbursement. More information on our benefits and perks can be found at:  

Censeo is an equal opportunity employer. We are committed to providing equal opportunity to all applicants and employees in full compliance with all applicable state and federal laws prohibiting discrimination on the basis of race, color, age, gender, religion, national origin, disability, protected veteran status, or any other class protected by applicable state or federal law.

Join Our Award-Winning Culture!

Our passion wins awards. But don’t just take it from us… 

  • 2020 Vault #21 Best Boutique Consulting Firm 
  • 2019 Ivy Exec #7 Best Boutique Consulting Firm 
  • 2018 Consulting Magazine Best Small Firms to Work For 
  • 2017 Vault #12 Best Boutique Consulting Firm 
  • 2016 Forbes Best Management Consulting Firms in America
  • 2015 Washington Business Journal’s Philanthropy List 

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