About the Job You're Considering
At Capgemini Invent, our Data Driven Transformation (DDT) team helps clients unlock the value of data, analytics, AI, and intelligent automation to drive measurable business outcomes. We combine consulting, data science, AI engineering, and industry expertise to deliver practical solutions that move from strategy to production.
As a Data Scientist, you will work as part of multidisciplinary teams to design, build, and deploy advanced analytics, machine learning, and AI solutions that solve complex business challenges. You will collaborate with business stakeholders, data engineers, AI engineers, and transformation consultants to create data-driven products and insights that accelerate enterprise transformation.
Your Role
- Develop and deploy machine learning, predictive analytics, and AI solutions to address client business challenges.
- Build, test, and optimize statistical models using structured and unstructured data.
- Work with large datasets from multiple sources to identify trends, patterns, and actionable insights.
- Collaborate with data engineers and AI engineers to operationalize models and support production deployment.
- Translate business requirements into analytical approaches, model designs, and measurable outcomes.
- Develop data visualizations, dashboards, and storytelling materials that communicate insights to technical and non-technical audiences.
- Support Generative AI and advanced analytics initiatives, including LLM-enabled use cases and intelligent automation solutions.
- Contribute to client workshops, solution design sessions, and proposal development activities.
Your Skills + Experience
- 5-8 years of experience delivering advanced analytics and AI solutions in consulting or industry environments.
- Experience leading analytical workstreams and managing stakeholder expectations.
- Hands-on experience deploying machine learning solutions in production environments.
- Experience designing AI-enabled products, cloud-native analytics solutions, or enterprise-scale data science initiatives.
- Ability to mentor junior team members and guide best practices in model development and experimentation.
- Experience presenting findings and recommendations to client leadership.
- Master's degree preferred in Data Science, Artificial Intelligence, Computer Science, Engineering, or a related field.
The base compensation range for this role in the posted location is: $100,500 - $189,890.
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, 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
