Data Scientist

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.

Responsibilities

• Develop, evaluate, optimise, and deploy machine learning models supporting real-time or operational traffic incident management use cases, such as anomaly detection, predictive classification, forecasting, or computer vision.
• Manage the ML model lifecycle, including data preparation, model development, evaluation, deployment, monitoring, retraining, and version management.
• Design and develop Agentic AI systems using LLM orchestration frameworks such as LangChain, LangGraph, or equivalent, including multi-agent coordination, routing, state management, tool use, and multi-step reasoning.
• Develop Agentic AI solutions for real-time or operational traffic incident management, including automated decision support and intelligent workflow automation.
• Integrate and fuse heterogeneous data sources, including structured and unstructured data, batch and streaming data, geospatial data, traffic sensors, CCTV/video, telemetry, and crowdsourced feeds.
• Develop and apply appropriate data fusion methodologies to extract reliable signals and insights from multiple real-time data sources.
• Implement and maintain MLOps practices and infrastructure, including model deployment pipelines, automated retraining, model monitoring, drift detection, and deployment standards.
• Define and monitor measurable outcomes for ML, Agentic AI, and data fusion solutions, including model performance, latency, automation rate, data throughput, and operational improvements.

Requirements

Experience

• At least 3 years of relevant experience as a Data Scientist, Machine Learning Engineer, AI Engineer, or equivalent.
• Experience delivering data science and AI solutions in production, proof-of-concept (POC), or proof-of-value (POV) environments.

Machine Learning & Model Development

• Hands-on experience developing, deploying, and optimising at least 2 machine learning models in a production, POC, or POV environment, with quantifiable performance outcomes using appropriate metrics (e.g. accuracy, precision, recall, F1-score, latency, or RMSE).
• Experience applying machine learning to real-time or operational traffic incident management, such as anomaly detection, predictive classification, forecasting, or computer vision on live data streams.
• Experience with MLOps, including building automated retraining pipelines or model drift monitoring systems, with ownership of deployment standards and tooling decisions (e.g. MLflow, Kubeflow, SageMaker) and quantifiable outcomes evidenced (e.g. model uptime, retraining frequency, deployment turnaround time).

Agentic AI System Design & Development

• Hands-on experience designing and deploying at least 2 agentic AI systems incorporating LLM orchestration (e.g. LangChain, LangGraph, or equivalent frameworks) in a production, POC, or POV environment, with quantifiable outcomes evidenced (e.g. task automation rate, reduction in manual intervention, latency benchmarks met).
• Experience designing multi-agent architectures incorporating agent coordination, routing, state management, tool use, and multi-step reasoning, applied to a real-time or operational traffic incident management use case.

Data Fusion & Heterogeneous Data Sources

• Hands-on experience integrating at least 2 heterogeneous data sources (e.g. structured/unstructured, batch/streaming) across at least 2 projects in a production, POC, or POV environment, with quantifiable outcomes evidenced (e.g. data throughput, data latency reduction, fusion accuracy, or volume of data sources integrated).
• Experience working with specialised data types such as geospatial data, sensor data, CCTV/video, or real-time telemetry streams, with clear description of the data fusion methodology applied.

Added Advantage

• Experience with traffic, transport, operations control centre, or incident-management systems.
• Experience deploying ML and Agentic AI solutions using cloud and containerised environments.
• Experience working with Singapore Government or public-sector data and systems.

Let's talk about what's in it for you!

Passionate people are Capgemini's Ace of Spades - join us to discover a career that will challenge, support and inspire you. Working at Capgemini you'll find the rewards are more than just financial. You will work alongside some very smart and inspiring people on exciting projects and you will also enjoy incredible benefits. We offer flexible work practices and 40 hours of self-development every year with a huge selection of learning opportunities to choose from.

As 'Architects of Positive Futures', Capgemini actively supports the community in 3 ways:

Diversity and Inclusion - we believe diversity of thought fuels excellence and innovation, which is why we positively encourage applications from suitably qualified candidates regardless of their gender identity, ethnicity, sexual orientation, religion, ability, intersex status or age. To support our commitment to diversity and inclusion, we celebrate special events and days of significance that are important to our employees such as Diwali, Bastille Day, Pride, IDAHOBIT, IWD and International day of people with Disabilities. Our Employee Resource Groups Women@Capgemini and OutFront support the grassroots passion of employees to drive our diversity agenda and effect change.

Digital inclusion - at Capgemini we are using our skills to drive social impact initiatives focusing on helping society address the impact of the digital and automation revolution. We also provide employees with opportunities to give back to the community through charity projects and volunteer days.

Environmental Sustainability - Capgemini joined the CDP's (Carbon Disclosure Project) prestigious 'A list' for its commitment to the Net-Zero economy. We are focusing on helping our clients transform towards more sustainable business models and committing to reduce our own carbon emissions (GHG) by 20% per employee by 2020.

Recognized by Ethisphere as one of the World's Most Ethical Companies for the last 8 years in a row, ethics and values are at the heart of Capgemini's corporate culture and business. Embedded in our DNA, our seven values - Honesty, Boldness, Trust, Team Spirit, Freedom, Fun and Modesty - have remained the same since company inception in 1967. To see how we bring these values to life, click here to listen to some of our employee’s stories.

Come join us, bring your whole self to work, create new possibilities for you, your customers and your community and help us to be Architects of Positive Futures.