> Markdown version of [/jobs/ext/1487545-data-scientist-iot-streaming-data-digital-m-s-accelerator](https://www.wearedevelopers.com/jobs/ext/1487545-data-scientist-iot-streaming-data-digital-m-s-accelerator). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - IoT & Streaming Data (Digital M&S Accelerator) - **Company:** Sanofi - **Location:** Lyon County, KS, United States (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Code Review, Databases, Continuous Integration, Data Cleansing, Data Transformation, Python (Programming Language), Machine Learning, Message Queuing Telemetry Transport (MQTT), Power BI, Signal Processing, Software Engineering, Data Streaming, Tableau (Software), Google Cloud, High Performance Computing, Large Language Models, Apache Spark, Deep Learning, Generative AI, Matplotlib, Information Technology, Influxdb, Real Time Data, Plotly, Apache Kafka, Spark Streaming, Machine Learning Operations, Virtual Agents, Software Coding, Streamlit Framework, Software Version Control, GXP, Unsupervised Learning, Databricks - **Published:** July 29, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p8bk3bxl9i ## About the Role You're a capable data scientist with a few years under your belt, genuinely excited by physical-world data - sensors, signals, and the machines that produce them. You can take a problem from vague business need to deployed model with limited hand-holding, and you've got a keen eye for improvement opportunities., * Hands-on track record working with IoT data, sensor streams, or time-series (this is what we care about most) * Demonstrated experience applying machine learning to real problems, ideally involving signals or temporal data * Experience developing deployable code and taking models to production in an agile environment * You're not put off by messy, real-world data - a big part of this role is turning inconsistent legacy data into something usable, and doing it well is where a lot of the value sits * Knowledge of the pharmaceutical or chemical domain is a huge advantage - understanding of manufacturing processes, GxP, or lab environments will set you apart Soft Skills * Excellent written and verbal communication skills * Experience working with multiple teams to drive alignment and results * Service-oriented, flexible, positive team player * Self-motivated, takes initiative * Problem solving & critical thinking Technical Skills * Strong Python, and comfortable with at least one database system - time-series databases (e.g. InfluxDB, TimescaleDB) especially valued * Solid command of time-series methods - forecasting, anomaly detection, signal processing - on streaming data * Working knowledge of streaming / real-time data technologies (e.g. Kafka, Spark Streaming, MQTT or similar) * Strong ML foundations: supervised/unsupervised learning, deep learning, with a solid grasp of the underlying theory * Comfortable working in cloud and high-performance computing environments (AWS, GCP, Databricks, Apache Spark) * Good software engineering practices - version control, testing, CI/CD, orchestration * Experience with data visualisation tools (Power BI, Tableau, Streamlit, Plotly, seaborn, or similar) * Experience handling sensitive data in critical environments (healthcare, etc.) * Familiarity with LLMs, RAG, or agentic workflows is a plus, not a requirement Education * Master's degree (or PhD) in engineering, computer science, mathematics, physics, statistics, or a related quantitative discipline with strong coding skills - backgrounds in chemical/process engineering, control systems, or signal processing are especially welcome Languages * English and French ## Description * Partner with business teams to understand requirements and translate them into technical solutions, working with a good degree of autonomy * Own the ingestion, cleaning, and harmonisation of IoT and sensor data from a mixed estate - some fully connected and streaming, plenty of it legacy, manual, or messy. A meaningful part of the role is data cleaning and wrangling: it's the foundation everything is built on, and doing it well is genuinely high-impact here * Design and deliver time-series models - forecasting, anomaly detection, and monitoring - on streaming sensor data to drive manufacturing performance and quality * Design, build, and support real-time and streaming data pipelines together with engineers and MLOps, and help bring legacy sites up to a usable state * Write highly optimised, production-ready code, taking models from experiment through to deployment * Scope, define, and deliver AI-based data products end to end, using data analysis, visualisation, and storytelling * Be accountable for the robustness of the AI solutions you deliver, applying responsible AI practices (monitoring, explainability, trustworthiness, ethics) * Contribute to - and help raise the bar within - the global data science community of practice * Support junior data scientists and analysts with informal guidance and code review _You'll also work across the wider AI portfolio - including LLMs, Retrieval-Augmented Generation (RAG), and agentic AI workflows - as our products increasingly blend sensor intelligence with GenAI. Strong here is a plus, but IoT and time-series is the core of this role. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Solving the puzzle: Leveraging machine learning for effective root cause analysis](https://www.wearedevelopers.com/videos/1518-solving-the-puzzle-leveraging-machine-learning-for-effective-root-cause-analysis) - [Designing How Work Feels: The Science Behind Sanofi’s Workplace Experience](https://www.wearedevelopers.com/videos/1848-designing-how-work-feels-the-science-behind-sanofi-s-workplace-experience) - [Vision for Websites: Training Your Frontend to See](https://www.wearedevelopers.com/videos/1213-vision-for-websites-training-your-frontend-to-see) ## Related Articles - [Best Companies to Work For in Paris: Top 25 Companies in 2023 ](https://www.wearedevelopers.com/magazine/190-best-companies-to-work-for-in-paris-top-25-companies-in-2023) - [Best Companies to Work For in France: Top 25 Companies in 2023 ](https://www.wearedevelopers.com/magazine/189-best-companies-to-work-for-in-france-top-25-companies-in-2023) - [Jobs in Tech: The State of the European Market](https://www.wearedevelopers.com/magazine/575-jobs-in-tech-the-state-of-the-european-market) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)