Kearney Activate - Data Scientist

Kearney · Washington · $90,000–$130,000 (stated in the posting)

Apply on the company website

About the Role

As a Data Scientist, you're building genuine hands-on data science skills across the full CRISP-DM lifecycle — business understanding, data understanding, feature engineering, and statistical modeling. Data science is the job here, not a data-analyst-plus-business-analyst-plus-QA blend. You'll work with strong SQL and Python, applying real statistical modeling and exploratory data analysis to real business problems — school or project-based ML/EDA experience is a perfectly acceptable starting point. Around that core, you'll be capable of client-facing discussions and translating requirements into modeling tasks, and your delivery proof point is data/model validation rigor — UAT test cases, model development and validation — not front-end QA. You'll work closely with our dedicated data architecture team, and with our senior Data Scientist / Product Engineer on more complex problems, growing toward that role over time.

What you'll do

Work hands-on across the CRISP-DM lifecycle: business understanding, data understanding, feature engineering, and statistical modeling

Apply strong SQL and Python to real data problems — exploratory data analysis, data preparation, and model building

Build and evaluate statistical and machine learning models under guidance from senior technical staff

Validate models and data rigorously: write UAT test cases and own data/model validation and automated validation scripts — using tools like Pytest and RTF for model/data validation automation — rather than front-end QA

Participate in client-facing discussions, translating business requirements into concrete modeling tasks

Collaborate with our dedicated data architecture team on data understanding and feature engineering, without owning deep pipeline architecture

Apply modern AI/GenAI tools in your data workflows — coding assistants, LLM-assisted EDA, and similar — as a practical, everyday skill

Document your work clearly enough for both technical and non-technical audiences to follow

Who you are

After nearly 100 years, we know this business is fundamentally about making connections — between facts, technologies, and above all, people. We look for collaborative, inquisitive problem-solvers who don't accept the first thing in front of them, who are always unapologetically themselves, and who take real ownership of the rigor behind their models and data.

In addition, we look for individuals with the following experience or qualities:

Roughly 0-3 years of experience in data science, analytics, or a related hands-on modeling role — school or project-based ML/EDA experience is genuinely acceptable in place of professional tenure

Strong, demonstrated SQL and Python skills, with real exposure to statistical modeling and exploratory data analysis

Comfortable across the CRISP-DM lifecycle — business understanding through feature engineering and modeling — rather than narrowly focused on one stage

A genuine quality mindset for model and data validation — attention to detail and a habit of double-checking rather than assuming

Capable of client-facing discussions, translating business questions into modeling tasks

Real business acumen: even in a technical role, comfortable in front of a stakeholder. Forge pods are small, and everyone contributes to the client relationship

Industry-vertical background (aerospace & defense, large-scale/heavy construction, manufacturing, supply chain, or S&OP) is helpful but not required at this level — it becomes a requirement as you grow toward the senior Data Scientist role

Comfortable operating in fast-paced, iterative, client-facing environments

Strong written and verbal communication skills

Comfortable using modern AI/GenAI tools day to day, or eager to build that fluency quickly

English fluency

Required qualifications

Ability to obtain, or current possession of, a U.S. Secret security clearance is required; an active or prior clearance is a strong plus

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field — or equivalent demonstrated experience; school or project-based ML/EDA experience is acceptable in place of professional experience

Technical skills and tools

Core (expected):

CRISP-DM lifecycle fundamentals (business understanding, data understanding, feature engineering)

Statistical modeling and exploratory data analysis

Strong SQL and Python

Basic data pipeline and relational data-modeling literacy

Preferred / a plus:

Pytest and RTF in particular for model/data validation automation

Exposure to ETL tooling or a cloud data platform (AWS, Azure, or Google Cloud)

Git-based version control familiarity

Basic exposure to LLM-assisted EDA or GenAI-assisted analysis workflows

Location

Washington, D.C. or Arlington preferred.

Boston and other East Coast hubs will be considered.

Must be able to work closely with the team and travel to client delivery sites as required.

U.S.-based only.

  What we can offer you

Every day, our people work to be the difference for our clients, our communities, and our colleagues. Helping them make an impact, they are sustained by a competitive remuneration package plus comprehensive benefits and perks, including but not limited to:

Generous retirement and pension savings contributions.

Comprehensive medical insurance for employees and immediate family.

Gym membership discounts.

Non-partner equity-based awards for consulting managers and above.

Structured and on-the-job learning and development opportunities.

Personalized opportunities including talent mobility, flexible work programs, and externships to help you chart a unique career journey.

Compensation Range: $90k-$130k: It is important to note that at Kearney, it is not typical for an individual to be hired at the top of the range for their role. Individual salaries within each

More jobs at Kearney · Data & Analytics jobs in Washington DC