Data Scientist - Manager - Energy & Commodities

Company Description

Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of the next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value.

Overview

Publicis Sapient is looking for a Data Science to join our team of bright thinkers and doers.You’ll use your problem-solving creativity to figure out our client’s most complex and challenging problems across different industries. We are on a mission to transform the world, and you will be instrumental in shaping how we do it with your ideas, thoughts, and solutions

Qualifications

Responsibilities

• Partner with product and business teams to understand challenges, identify opportunities, and frame problems where AI and machine learning can deliver measurable value• Evaluate and select the most suitable AI approaches, including LLMs, RAG systems, classical ML, or multimodal AI• Design and build machine learning pipelines, from experimentation and prototyping to production deployment• Develop, fine-tune, and optimize AI models (including LLMs and generative AI models) while ensuring scalability, performance, and responsible use of AI• Set up and maintain AI/ML development and production infrastructure, leveraging MLOps best practices (CI/CD, monitoring, observability, model versioning)• Build robust data ingestion, transformation, and feature engineering pipelines to support high-quality AI applications• Identify and curate high-value training datasets, leverage transfer learning, and adapt pre-trained models to business-specific contexts• Create APIs, integrations, and tools that enable stakeholders to operationalize AI insights in real-time environments• Help stakeholders understand AI outcomes, limitations, and trade-offs, ensuring transparency, interpretability, and alignment with business goals• Continuously research and recommend emerging AI capabilities (LLMs, multimodal models, autonomous agents) that can improve products or processes

Qualifications

• Strong experience designing, developing, and deploying AI/ML products or models in production• Strong programming skills in Python• Solid experience with data manipulation and ML tooling: NumPy, Pandas, scikit learn, etc• Proven experience building and fine-tuning models with TensorFlow, PyTorch, Keras• Hands-on experience with LLMs, RAG systems and vector databases• Familiarity with NLP, generative AI, prompt engineering, embeddings, and multimodal architectures• Strong understanding of data science methodology, applied statistics, ML/DL, and AI evaluation frameworks• Experience with MLOps and cloud-native development: Docker, Kubernetes, CI/CD, feature stores, model monitoring• Practical experience with cloud AI platforms• Strong algorithmic and problem-solving skills, with the ability to deliver end-to-end solutions under time constraints

• German speaking (C1 at least)

• Consulting background; Background in the Energy and Commodities or Financial Services sector is a plus

Additional Information

Set Yourself Apart With

• Experience defining AI or data strategies for organizations

• Hands-on experience with modern AI tools (e.g., generative AI, copilots, automation platforms)

• Exposure to data architecture, data engineering, or product development

• Track record of driving AI adoption or innovation initiatives within organizations

• Advanced degree in a relevant field (e.g., data science, engineering, business, or similar)

What We’re Looking For

We’re looking for someone who is:

• Equally comfortable in the boardroom and with a dataset

• A translator between business ambition and technical reality

• Curious, adaptable, and excited about the fast-moving AI landscape

• Motivated to go beyond pure data science into broader problem-solving and innovation