Kearney Activate - Data Scientist

About the role

In this position, you will develop practical data science skills throughout the entire CRISP-DM framework, which includes understanding business needs, data exploration, feature engineering, and statistical modeling. Your focus will be on applying SQL and Python to address real-world business challenges, emphasizing statistical modeling and exploratory data analysis. You will engage in client interactions and translate their requirements into actionable modeling tasks, ensuring the validation of your models and data.

Key facts

What you'll do

• Engage in hands-on activities across the CRISP-DM lifecycle, from business understanding to feature engineering and modeling.
• Utilize SQL and Python to tackle data-related challenges, including exploratory data analysis and model creation.
• Collaborate with senior technical staff to build and assess statistical and machine learning models.
• Conduct thorough validation of models and data by writing UAT test cases and managing data/model validation scripts using tools like Pytest and RTF.
• Participate in discussions with clients, converting their business inquiries into specific modeling tasks.
• Work alongside the data architecture team to enhance data understanding and feature engineering without delving into deep pipeline architecture.
• Integrate modern AI/GenAI tools into your daily data workflows, such as coding assistants and LLM-assisted exploratory data analysis.
• Document your processes clearly for both technical and non-technical stakeholders.

Requirements

• 0-3 years of experience in data science, analytics, or a similar hands-on modeling role; academic or project-based experience in ML/EDA is acceptable.
• Proficient in SQL and Python, with practical experience in statistical modeling and exploratory data analysis.
• Familiar with the entire CRISP-DM lifecycle, demonstrating a broad understanding rather than specialization in one area.
• Strong attention to detail and a quality-focused mindset for model and data validation.
• Effective in client-facing scenarios, able to translate business questions into modeling tasks.
• Basic business understanding, comfortable interacting with stakeholders.
• Background in industries such as aerospace and defense, construction, manufacturing, supply chain, or S&OP is beneficial but not mandatory at this level.
• Ability to thrive in fast-paced, iterative environments.
• Excellent written and verbal communication skills.
• Familiarity with modern AI/GenAI tools or a willingness to quickly learn.
• Fluency in English.

Required Qualifications

• Must have or be able to obtain a U.S. Secret security clearance; an active or prior clearance is advantageous.
• 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.

Skills & tools

• Fundamentals of the CRISP-DM lifecycle (business understanding, data understanding, feature engineering).
• Statistical modeling and exploratory data analysis.
• Strong skills in SQL and Python.
• Basic understanding of data pipeline concepts and relational data modeling.

Nice to have

• Experience with Pytest and RTF for model/data validation automation.
• Familiarity with ETL tools or cloud platforms (AWS, Azure, or Google Cloud).
• Knowledge of Git for version control.
• Basic experience with LLM-assisted exploratory data analysis or GenAI workflows.

Practical notes

Kearney offers a competitive salary range of $90,000 to $130,000. It is important to note that new hires typically do not start at the upper end of this range. Salaries are determined by various factors, including education, experience, and skills. In addition to base salary, employees may be eligible for a discretionary performance bonus. Comprehensive benefits include paid time off, 401(k) matching, medical, dental, and vision coverage, and wellness programs.

Kearney is committed to fostering a diverse and inclusive workplace. We encourage applicants from all backgrounds to apply, ensuring that our team reflects the diversity of the communities we serve.