Entry Level - Data Scientist-GenAI Engineer -ML

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Job Description

 

About the Role You’re Considering

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.

 

 

Your Role:

• 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.

Job Description - Grade Specific

 

Roles & 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.

 

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

Educational Qualifications (Preferred)

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

 

 

The base compensation range for this role in the posted location is:$60,000 to $75,000.

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

 

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: 

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays,