The Data Science Standards Board

Companies seek talent who can help them understand and leverage the vast amount of information they collect every day. However, there’s a lack of transparency and defined paths to success in the field. The Data Science Standards Board works to:

  1. Define key roles and build transparent career pathways.
  2. Establish objective performance standards through industry-standard assessments.
  3. Facilitate hiring and develop talent at scale.

Certified Data Scientist

Our industry-led assessments cover the key skills required to succeed at specific career stages in data science.


    Technical Focus


Level 1

For data scientists who want to demonstrate essential skills.

Wrangling, exploring, modeling, and communicating data. View the skills rubric.

Level 2

For data scientists in data analytics roles.

Synthesizing data, testing, modeling, programming, business. View the skills rubric.

Level 2

For data scientists in data engineering roles.

ETL processes, data security, programming, optimization, business. View the skills rubric.

Level 2

For data scientists in research roles.

Research, survey, and model design, programming, business. View the skills rubric.

Level 2

For data scientists in machine learning roles.

Programming, modeling, productionizing, optimization, business. View the skills rubric.

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Redefining Data Science

Synthesizing insights from data leaders and providing transparency into career pathways.

DS Standards Board What Is A Data Scientist

What Is a Data Scientist?

“Data scientist” means different things to different people. To foster a common understanding, the Data Science Standards Board defines data science across four key components:


  • Acquiring, organizing, and delivering complex data.
  • Discovering relationships and anomalies among variables.
  • Building and deploying machine learning models.
  • Synthesizing data to influence decision making.
DS Standards Board Career Framework

The Data Science Career Framework

The Data Science Career Framework outlines growth options for data professionals, and helps individuals, teams, and business partners navigate this dynamic and vital field.

While all data scientists share foundational skills at Level 1, careers can mature into four Level 2 specialties aligned with the Board’s definition for data science. Fluency in three Level 2’s prepares an individual to advance to Level 3 leadership roles.

Read about our comprehensive framework.

Certified Data Scientist Credential Certificate Screenshot Jamie Harris

A New Standard for Data

The Certified Data Scientist Level 1 (CDS1) assessment tests skills in Level 1 of the Career Framework. It was developed in partnership with industry-leading executives from companies like Bloomberg, Booz Allen Hamilton, Spotify, and others who sit on the Data Science Standards Board. 


CDS1 helps individuals benchmark their abilities against industry standards and helps employers identify high-potential candidates. Only the top 20% of scorers will qualify for the CDS1 credential, which recognizes in-demand data skills.

Meet the Data Science Standards Board

DS Standards Board Meet The Data Science Standards Board

Learn About Our Board Members

Aaron Black, Chief Data Officer, Inova Translational Medicine Institute

Aaron Black is the chief data officer at the Inova Translational Medicine Institute (ITMI). ITMI was established in 2011 to provide precision medicine as part of Inova’s vision of being a destination health care provider in the greater Virginia and Washington, D.C. area. Previously, Aaron was the informatics manager and leader for the Biospecimen Core Resource at Nationwide Children’s Hospital for the National Cancer Institute's Cancer Genome Atlas project. He was co-architect for the flexible data model to store and access data from studies for more than 30 cancer subtypes, and clinical data from biobanks and academic institutions across five continents.

Aaron graduated from Miami University with degrees in accounting and management information systems, and studied international business at Miami’s Luxembourg campus. Aaron is a certified Project Management Professional and ScrumMaster, and has dozens of technical certifications from Microsoft and the Information Technology Infrastructure Library.

Michael Bopp, EVP, Chief Customer Engagement Officer, Synchrony Financial

Michael Bopp is currently executive vice president and chief customer engagement officer for Synchrony Financial. Previously, he was president and chief operating officer of Argus (a Verisk company) and responsible for the company’s financial services division. The financial services division comprised 500+ employees across more than 10 geographies serving 29 of the top 30 financial institutions. He joined Argus in 2010 and has more than 20 years of experience in the financial services industry.

Before Argus, Michael headed marketing and online analytics at TD Ameritrade. Earlier in his career, he worked at Citi Cards, performing various finance and decisions management functions. In 2003, he moved to GE Capital as head of pricing and analytics for GE Capital Retail Consumer Finance. Michael holds a master’s degree in industrial and organizational psychology from the University of Connecticut and a Bachelor of Arts in psychology from Johns Hopkins University.

Christine Hung, Head of Data Solutions, Spotify

Christine Hung leads the Data Solutions team at Spotify. Her team collaborates with business groups across the company to build scalable analytics solutions and provide strategic business insights. Prior to joining Spotify, Christine ran the Data Science & Engineering team at The New York Times, where her team partnered closely with the newsroom to build audience development tools and predictive algorithms to drive performance. Christine also previously worked at Apple as head of Sales Analytics at iTunes and at McKinsey & Company as a business analyst. She grew up in Taiwan, holds an MBA from the Stanford Graduate School of Business, and lives in Manhattan with her family.

John Larson, Senior Vice President, Booz Allen Hamilton

John Larson is a leader in Booz Allen’s Digital, Analytics, and Strategy practice serving civil and commercial clients. He leads the architecture and execution of analytic solutions providing analytic strategy advisory services including, fraud, waste, and abuse detection and mitigation; and artificial intelligence and deep learning services. 

For more than 20 years, John has been a champion and early adopter of advanced analytic solutions within the Federal Government, as well as energy and natural resources, chemicals and refined products, transportation, healthcare, and social welfare and pension programs. He has helped develop transformative and innovative solutions for federal clients. 

Prior to joining Booz Allen, John led advanced analytics initiatives and drove enterprise-wide innovation at IHS Markit, creating products and consulting solutions in the oil and gas, automotive, and maritime industries. He’s a recognized expert in analytic techniques such as predictive modeling, Bayesian statistics, natural language processing, and classification and clustering. 

John holds a double Bachelor of Arts in economics and history, and a master’s degree in public policy from The College of William & Mary.

Domenic Maida, Global Head of Global Data, Bloomberg L.P.

Domenic Maida is the global head of Bloomberg's Global Data department, which is at the heart of Bloomberg, and works closely with teams in engineering, sales, news, and more. In this role, which he’s held since 2013, he oversees the departments responsible for acquiring data and managing relationships with more than 350 exchanges, regulators, and trading venues.

Domenic began his career in 1995 as a software engineer at Bloomberg. He spent 13 years in Bloomberg’s Research and Development department, becoming its global manager in 2007. From 2008–2012, he held the position of global head of Bloomberg’s Terminal business, with responsibility for sales, customer support, and product development. Additionally, Domenic is a member of Bloomberg Swap Execution Facility Board (BSEF) and is the executive co-sponsor of Bloomberg’s Latino Community. He holds a Bachelor of Science in mechanical and electrical engineering from John Hopkins University.

Mainak Mazumdar, Chief Research Officer, Nielsen

Mainak Mazumdar leads the Nielsen Company’s data science organization. In this role, he supports new initiatives such as deploying RPD (return path data) into U.S. Local TV; launching Nielsen Total Audience; and globalizing eCommerce, Nielsen Digital Ad Ratings, and Nielsen AI. Mainak has also launched new competencies in big data, machine learning/AI, and data integration to deploy newer forms of methods in the company’s business.

Shane Murray, VP of Data Analytics and Platforms, The New York Times

Shane Murray is vice president of data analytics and platforms at The New York Times. In this position, he oversees the deployment of data analytics across the newsroom and product teams, where his team delivers audience insight in the form of reporting, exploratory and predictive analysis, experiment design, and optimization. Shane partners with data science and engineering teams to design and build the data platforms that support analytics across the enterprise.

Prior to joining The Times, Shane was an optimization and analytics consultant at Accenture, working with financial services, eCommerce, and telecommunications companies to build and scale test-and-learn programs within their organizations. During this time, Shane actively contributed to the methodology and development of multivariate testing software, and led optimization delivery teams focused on the execution of test-and-learn programs.

Antonia Tartamella, Vice President of Data Science, Hilton

Antonia Tartamella serves as the vice president of data science for Hilton. In her role, Antonia leads the Hilton data science roadmap to leverage AI and machine learning at scale across a range of opportunities, from delivering timely, personalized experiences for guests to providing industry leading capabilities for Hilton owners, operators, and hotels.

Prior to Hilton, Antonia served as the vice president of data engineering, analytics, and platforms for Comcast. At Comcast, Antonia served as a transformative leader, delivering both business and technology solutions with a focus on data analytics, data engineering, and data infrastructure. Antonia also spent time at 3M, and served as a business consultant in the manufacturing and telecommunications industries developing transformative data strategies that accelerated business goals.

Antonia holds two degrees from the University of Connecticut: a Bachelor of Arts in political science and government and a Master of Arts in political science and quantitative studies.

“We're excited to bring together these incredible leaders to explain what skills matter, and increase access to careers in data science."

Kieran Luke, General Manager Online & Standards, General Assembly

Frequently Asked Questions

Will the Data Science Career Framework and Skills Rubrics change over time?

The Board, in collaboration with GA, will review the framework and underlying content annually, and make changes if necessary.

Is coursework required to score well on the Certified Data Science Level 1 assessment?

No. However, GA will offer courses informed by the framework.

What’s the Board’s timeline for releasing data science skills assessments?

We launched the Certified Data Scientist Level 1 (CDS1) assessment in October 2018. The first round of Certified Data Scientist Level 2 assessments will launch in 2019.

Is the Data Science Career Framework U.S.-centric or global?

This is a framework developed with data science leaders of global companies. We anticipate the framework will have global relevance, although we expect the exact implementation of this framework to vary across organizations.

What do you mean by “standards”?

The Board’s standards are made up of the Certified Data Science assessments, Skills Rubrics, and Career Framework. These guidelines:

  1. Are comprehensive rather than being focused on one area or a specific platform.
  2. Provide structure in explaining data science career stages and paths.
  3. Lay out the skills of a successful worker in data science and how to validate those skills.
  4. Were devised and validated by leaders across a wide range of sectors. 
  5. Focus on the application of knowledge rather than on academic theory.

What’s the Board members’ role?

Our Data Science Standards Board’s goals are to:

  1. Set and explain standards for skills required to succeed in data science. 
  2. Approve assessments and certification requirements.
  3. Guide the profession toward transparent, competency-based career pathways.

What is General Assembly (GA)?

GA is a pioneer in digital education and career transformation. We work with global companies of all sizes — including more than 40 of the Fortune 100 — to solve talent gaps in the skills needed to thrive in an increasingly tech-driven economy. We’ve engaged with major employers including Capital One and L’Oréal to evaluate, train, and develop their workforces in anticipation of future business needs through reskilling, upskilling, onboarding, and hiring strategies.

What coding languages or tools do professionals need to know at each level of the Data Science Career Framework?

Please refer to our Skills Rubrics above to see the recommended languages and tools for each level.