Top Data Science Jobs in Paris

Lead Wiremind’s product organization and company-level strategy, overseeing approximately 15 Product and Design employees. Set product direction, align software and AI/ML roadmaps, improve product processes, unblock squads, enhance UX for complex expert-facing B2B SaaS products, and coach product leaders. The role focuses heavily on revenue management, forecasting, pricing, and transport products while partnering with the CEO and executive team.

The Chief Marketing Officer will lead Wiremind’s global go-to-market strategy across product, sales, customer success, and executive leadership. Responsibilities include product and market positioning, packaging and pricing alignment, demand generation, corporate communications, PR, thought leadership, sales enablement, performance measurement, and international growth. The role manages an 11-person marketing team, drives revenue-oriented metrics such as CAC, LTV, and pipeline contribution, and develops AI-enabled market intelligence and marketing operations.

Senior Data Scientist responsible for delivering data science and machine learning solutions using Databricks. The role involves translating business requirements into effective data-driven solutions, collaborating directly with French-speaking clients and technology teams, and owning projects through successful delivery. Strong analytical, communication, stakeholder management, French and English language skills are required. The position offers flexible hybrid work on AI, generative AI and data projects in an international environment.

Develop GreyNoise’s cybersecurity channel business across Europe by recruiting and activating partners, building joint business plans, enabling partner teams, generating qualified pipeline, and co-selling enterprise and government opportunities. The role manages partner relationships, channel strategy, revenue targets, forecasting, commercial negotiations, partner reviews, technical enablement, demand generation, and cybersecurity event representation.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Develop and deploy scalable, production-grade machine learning and AI solutions for financial research. Build LLM- and NLP-based applications, collaborate with senior engineers, and contribute to reliable AI-driven products. Responsibilities require Python, software engineering, deep learning, databases, Docker, and at least one major deep learning framework. Preferred experience includes RAG pipelines, vector databases, LLM fine-tuning, cloud platforms, and Kaggle competitions.

Supports enterprise software sales by presenting Aera’s Decision Intelligence platform, conducting tailored demos, leading proofs of concept and value, facilitating workshops, developing ROI analyses and business cases, responding to proposals and RFx requests, and defining deployment roadmaps. Partners with sales, product management, marketing, delivery, and customer success teams while engaging technical and executive stakeholders. The role requires supply chain expertise, consultative communication, and approximately 25% travel.

Lead enzyme screening and biocatalytic process development for small-molecule APIs. Apply reaction engineering, kinetic modeling, DoE, machine learning, and robotics to optimize and scale processes, transfer to pilot scale, document results, and drive digital transformation across international multidisciplinary teams.

Supports Pernod Ricard’s global Commercial Excellence team through market assessments, performance analysis, executive reporting, commercial standards, best-practice benchmarking, training materials, dashboards, and internal communications. Contributes to deployment of the D STAR machine-learning recommendation tool by monitoring roadmaps and KPIs, coordinating steering committees, prioritizing enhancements, and translating market needs into technology requirements. The role also supports strategic commercial frameworks and roadmap evolution.

Own and execute the roadmap for a core document verification product area, improve verification accuracy and conversion, partner with Engineering, AI/ML, Design, Growth and Ops, use analytics and experimentation to validate hypotheses, and prioritise investments while ensuring regulatory and compliance alignment.

Lead product strategy for Kard’s data and internal developer platforms across data, ML, analytics, engineering enablement, and infrastructure teams. Translate transaction data and platform capabilities into customer and commercial value through personalization, targeting, measurement, decisioning, and partner integrations. Define reusable platform capabilities, improve self-service and reliability, shape cross-functional bets, align stakeholders, and coach product leaders while balancing scale, security, privacy, compliance, and business impact.

As a PhD Investment & Strategy Associate, you'll conduct research and financial analysis focused on AI-driven technology companies, providing insights for investments while collaborating with a talented team to support strategic decision-making.

Design and execute benchmarks, curate datasets, evaluate benchmarks, and build evaluation infrastructure for AI model assessment while collaborating with R&D.

Serve as a pre-sales applied AI architect partnering with GSIs and cloud providers (AWS/GCP) to develop joint GenAI solutions, codify reference architectures, support strategic customer deals, enable partner developer communities, and provide product feedback to inform roadmap and partner strategy.

Develop and demonstrate NVIDIA GenAI solutions on hyperscaler infrastructure, primarily GCP. Advise customers and partners, optimize GPU-accelerated training and inference pipelines, conduct proof-of-concept evaluations, and collaborate with Engineering, Product, Sales, and Marketing teams to integrate NVIDIA technologies into enterprise architectures.

Design, prototype, evaluate, and ship AI agents and reusable skills for product and analytical challenges. Build agent evaluators, guardrails, golden datasets, retrieval systems, and LLM-powered diagnostics. Collaborate with Product, R&D, GTM, and Design teams to frame ambiguous problems, analyze large datasets, develop predictive models, and create actionable insights. The internship requires a builder mindset, strong analytical ability, and proficiency in Python, SQL, data pipelines, and visualization.

Lead GTM strategy and product positioning for key products, create messaging and content, run campaigns and launches, analyze market and competitive trends, and collaborate cross-functionally to drive adoption, pipeline growth, and customer engagement.

Lead and deliver data science projects: perform exploratory and advanced analyses, validate and optimize predictive models, build dashboards and visualizations, ensure data governance, coordinate local/global solutions, present insights to stakeholders, and mentor junior analysts to support commercial decision-making.

The Lead Golang Software Engineer develops server solutions, leads technical designs and code reviews, mentors colleagues, and ensures the quality of engineering practices in the Commercial Systems unit.

Lead end-to-end data efforts: translate business needs into analytics, build forecasting and ML models, create dashboards, automate pipelines, monitor models, and drive data-driven product features.

Data Scientists at QuantCo will analyze data, build machine learning models, and communicate results to stakeholders, aiming for impactful solutions.

As a Data Science Intern, you'll identify frameworks for data-driven business challenges, transform datasets, run analyses, build machine learning models, and communicate results.

Develop and refine NLP projects by improving LLM models, implementing production models, and conducting performance experiments.

The internship involves deploying data processing pipelines, collaborating with clients, conducting R&D in AI and data science, and supporting sales efforts.