Job Location : Cary, NC (Onsite/Hybrid from Day 1)

Job Description

We are seeking an experienced Data Scientist to join our growing Analytics and AI team. This role is responsible for developing and deploying advanced Machine Learning, Artificial Intelligence, and Generative AI solutions that drive customer engagement, marketing effectiveness, revenue growth, and business outcomes. The ideal candidate will have a strong blend of technical expertise, business acumen, and stakeholder management experience, particularly within the insurance and/or financial services industry.

Key Responsibilities

• Own technical decisions, project outcomes, timelines, and production stability within assigned business domains.
• Design, develop, train, and optimize machine learning and deep learning models for marketing, customer engagement, sales, and business analytics use cases.
• Analyze complex datasets to identify trends, patterns, anomalies, and actionable insights that support business strategy and decision-making.
• Develop statistical models, predictive analytics, and machine learning algorithms using Python and Azure cloud technologies.
• Build, deploy, and support production-ready ML and GenAI solutions, including API-based, batch, and real-time inference applications.
• Collaborate with business stakeholders, product teams, and cross-functional partners to identify opportunities and implement data-driven solutions.
• Integrate AI and ML capabilities into business applications and workflows through APIs, SDKs, and microservices.
• Create compelling visualizations, dashboards, reports, and presentations to communicate analytical findings and recommendations to senior leadership and business partners.
• Apply MLOps best practices to ensure scalability, reliability, performance monitoring, and operational excellence of AI/ML solutions.
• Optimize platform components leveraging cloud-native architectures, distributed computing, and efficient resource management practices.
• Stay current with emerging trends, technologies, and best practices in Artificial Intelligence, Data Science, Machine Learning, and Generative AI.
• Promote responsible AI practices, including data privacy, model governance, bias mitigation, and model monitoring.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field.
• 8+ years of experience in Data Science, Machine Learning, Artificial Intelligence, and/or AI/ML Engineering.
• 5+ years of experience in the Insurance and/or Financial Services industry with exposure to sales, marketing, customer engagement, or customer analytics.
• Proven experience designing, deploying, and operating production Machine Learning and/or Generative AI solutions, including APIs, batch processing, and real-time inference.
• Strong experience developing Machine Learning models using Python, preferably in cloud environments.
• Experience with Azure Machine Learning, Domino Data Lab, Power BI, or similar analytics and ML platforms.
• Strong SQL skills and hands-on experience with data analysis, anomaly detection, data validation, and Exploratory Data Analysis (EDA).
• Solid understanding of statistics, mathematics, predictive modeling, machine learning algorithms, and data science methodologies.
• Experience leveraging AI and predictive analytics to improve customer experience, communication strategies, revenue generation, marketing effectiveness, and other business outcomes.
• Familiarity with responsible AI principles, including data privacy, bias mitigation, model explainability, governance, and monitoring.
• Excellent written and verbal communication skills, including the ability to present insights effectively through storytelling, visualizations, and executive-level presentations.

Preferred Qualifications

• Experience with Generative AI, Large Language Models (LLMs), and modern AI frameworks.
• Experience implementing MLOps and model lifecycle management practices in cloud environments.
• Knowledge of cloud-native architectures and scalable AI/ML deployment patterns.
• Experience working within highly regulated environments such as Insurance or Financial Services.

The base compensation range for this role in the posted location is: 85786- 97273

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