Entry Level - Data Scientist-GenAI Engineer -ML

Capgemini • Seattle, WA

19h • $60,000 - $75,000

About The Position

The Data Scientist / Machine Learning Engineer will leverage strong expertise in machine learning algorithms—such as Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Trees, Random Forest, Gradient Boosting Machines (GBM), Deep Neural Networks (DNN), Naive Bayes, and Support Vector Machines (SVM)—to lead projects, collaborate with cross-functional teams, and engage with customers to deliver impactful AI-driven solutions.

Requirements

• Basic understanding of machine learning concepts and algorithms:
• (e.g., Linear Regression, Logistic Regression, Decision Trees, Clustering)Proficiency in Python and familiarity with data science libraries
• (e.g., Pandas, NumPy, scikit-learn)Exposure to data visualization tools (e.g., Matplotlib, Seaborn, or similar)Fundamental knowledge of statistics and data analysis techniquesBasic understanding of SQL and data querying conceptsWillingness to learn cloud platforms, ML tools, and deployment practicesStrong analytical and problem-solving skillsGood communication skills and ability to work in a team-oriented environment

Nice To Haves

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field

Responsibilities

• Assist in building and testing machine learning models using supervised and unsupervised learning techniques.
• Support data preprocessing activities, including data cleaning, transformation, and feature creation.
• Work with structured and unstructured datasets to support analytics and modeling initiatives.
• Collaborate with senior data scientists and machine learning engineers on model development and evaluation.
• Perform basic exploratory data analysis (EDA) to identify trends and insights.
• Help document models, data sources, and processes for transparency and reusability.
• Participate in deploying models to development or testing environments under guidance.
• Monitor model performance and support retraining activities as needed.
• Work closely with cross-functional teams such as data engineering, software development, and product teams.
• Stay up to date with basic machine learning concepts, tools, and industry best practices.
• Develop and implement AI-assisted marketing analytics solutions that address customer needs through data science and machine learning.
• Collaborate closely with cross-functional teams to deliver innovative solutions that drive business growth and enhance customer engagement.

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees