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Data Scientist
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$102k-125k (estimate)
Full Time 1 Week Ago
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Censeo Consulting Group is Hiring a Data Scientist Near Washington, DC

Data Scientist

Introduction

Censeo Consulting is seeking a Data Scientist to support our client at the General Services Administration (GSA). We are looking for an experienced individual with strong knowledge of SQL, AWS Cloud Services, Mongo DB MQL, and exceptional ability to problem-solve abstract issues based on client needs. In the role you will have opportunities to work with Big Data, supporting the synthesis and understanding of Billions of Dollars and Millions of rows of data for the client. Some key responsibilities will include:

Identify, clean, and normalize Transactional Data Reporting (TDR) data, Contractor Payment Reporting Module (CPRM) and other data sets.

Build data models that standardize 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

3 years of experience in a Data Science role and a (BS/MS/PhD) in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Computer Science, or another strong quantitative field is required.

High proficiency with Python in a variety of settings.

High proficiency with PySpark or Scala within a Spark environment to manipulate data and draw insights from large data sets.

Strong problem-solving and communications skills and ability to work with clients to understand their needs and develop unique solutions utilizing data science expertise.

Proficiency in using Amazon Web Services (AWS), Amazon Simple Storage Service (Amazon S3), Amazon EMR (previously called Amazon Elastic MapReduce), and Redshift.

Proficiency in AWS Cloud Services and SQL.

The ability and desire to work independently and structure work based on client requirements.

Experience using GitHub for version control and understanding of modern coding standards and commitment to building sustainable code.

Strong understanding of core statistical concepts: mean, median, mode, regression analysis, sampling theory, hypothesis testing, etc.

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 skills to work with clients and interdisciplinary teams to comprehend the customer experience, define relevant qualitative and quantitative measurements, uncover actionable insights, and identify opportunities for gaining and retaining clients.

Additional Preferred Experience

Ability to produce high quality figures and graphs and ability to interact with Tableau.

Proficiency with Alation and MongoDB MQL.

Knowledge and experience with Large Language Models.

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 (including unstructured data sets) and processes to lead new transformation efforts for customer experience.

Position Responsibilities:

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

Data scientist support currently provides MAS data modeling that standardizes the structure and relationships of SRP data with other key data sets across the enterprise that can be used by multiple portfolios. Additional data scientist support is needed for data management and data quality enhancement activities aligned to the FSS19 Phase 3 Modernization project as well as similar activities focused on implementing the FAS Contract Data Strategy (CDS). This work will include:

Engaging with Domain Stewards to ensure initial metadata provided for data sources is complete, coordinating with Domain Stewards to periodically update for new requirements and/or new data elements, and support Domain Stewards in updating metadata in Alation data catalog as required.

Providing direct support for FAS data governance and data architecture in integrating data sources into FAS processes, standards and data catalog including assessing the alignment of FSS19 data/reports to systems receiving data/report feeds and to EDA data sources.

Providing recommendations on compulsory metadata requirements and updates to data catalog structure/workflows to maintain FAS data model

Conducting a metadata quality assessment of all FAS data assets in the EDA data catalog.

Communicating with the FAS community on the status of data governance processes/procedures and availability of data within AWS S3 data lake and EDW. Maintain awareness of all data ingestion progress and priorities as well as the status of all data sources

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 youll join a tight-knit community of 50 brilliant and passionate colleagues. We are advocates for a better functioning public sector, and were also good friends who know the names of each others 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 Fine Print:

Expected travel 0-10%; may?increase based on business needs

This is an exempt, full-time position

Location: Washington D.C. area with Hybrid/Remote flexibility

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: https://www.censeoconsulting.com/about/join-us/.

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 dont just take it from us

2023 Vault #9 Best Consulting Firm for Work/Life Balance

2023 Vault #23 Best Consulting Firm for Overall Diversity

2023 Management Consulted #3 Best Boutique Firms in Washington DC

2022 Vault #41 Best Overall Consulting Firm to Work For

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 Journals Philanthropy List

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Job Summary

JOB TYPE

Full Time

SALARY

$102k-125k (estimate)

POST DATE

04/18/2024

EXPIRATION DATE

05/04/2024

WEBSITE

censeoconsulting.com

HEADQUARTERS

WASHINGTON, DC

SIZE

25 - 50

FOUNDED

2013

TYPE

Private

CEO

JEFFREY M YOUNG-BEY

REVENUE

$5M - $10M

INDUSTRY

Religious Organizations

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The following is the career advancement route for Data Scientist positions, which can be used as a reference in future career path planning. As a Data Scientist, it can be promoted into senior positions as a Data Scientist IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Data Scientist. You can explore the career advancement for a Data Scientist below and select your interested title to get hiring information.

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If you are interested in becoming a Data Scientist, you need to understand the job requirements and the detailed related responsibilities. Of course, a good educational background and an applicable major will also help in job hunting. Below are some tips on how to become a Data Scientist for your reference.

Step 1: Understand the job description and responsibilities of an Accountant.

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Step 2: Knowing the best tips for becoming an Accountant can help you explore the needs of the position and prepare for the job-related knowledge well ahead of time.

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Analyzing data from multiple angles and searching for trends that could reveal problems or opportunities.

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Data scientists lay a solid foundation to help perform all kinds of analysis.

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Data scientists are also expected to have stronger software engineering skills that data analysts.

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Business analysts are focused on reporting, just like data analysts.

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Step 3: View the best colleges and universities for Data Scientist.

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