Sekoia

Data Scientist Engineer

Sekoia Rennes, Brittany, France

Computer and Network Security · 51-200 employees

Jul 01
Mid (2-5 yrs) Contractor France
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About the role

You will build and operate scalable data platforms while developing and deploying advanced algorithmic models into production. This role involves harmonizing heterogeneous data sources and ensuring the performance and quality of data pipelines across the company.

What they look for

Python Data Engineering Data Science SQL Pandas Scikit-learn Machine Learning Algorithms Airflow MLOps Continuous Integration Statistical Modeling Data Pipelines Software Engineering PySpark

Requirements

Candidates should hold a Master's degree or higher and possess 3 to 5 years of experience in data science and software development. Proficiency in Python, SQL, and machine learning algorithms is required, along with a strong engineering mindset for production-grade code.

Full description

You will join our Data team, currently in its maturation phase, with a twofold challenge: industrializing a platform able to absorb massive real-time volumes (1,000,000 events per second), and turning that critical mass of information into tangible product value.

This role deliberately straddles two worlds:

  • Within the Data team, you build and harden the pipelines that feed the entire company.
  • As reinforcement for our tech and product squads, you join pitches that call for genuine mathematical, statistical and algorithmic depth: designing, adapting and implementing the advanced algorithms behind the features we want to build and then shipping them to production

yourself.

This is a role for someone who dislikes the border between the notebook and the running service: you design the algorithm, you write it properly, you deploy it, you monitor it.

Your missions:

Build and operate the data platform (Data Engineer hat)

  • Design and implement in Python data processing workflows, from development to production.
  • Centralize and harmonize heterogeneous sources (Product, Finance, Marketing) to make data accessible and reliable for all Sekoia teams.
  • Develop, test, and orchestrate pipelines (via Airflow).
  • Act as a curator of the data, collecting and enriching the business data generated day after day by our automated sensors and our analysts.
  • Monitor and guarantee the quality and back-end performance of production.

Bring algorithmic value to the product squads (Data Scientist hat)

  • Join a squad for the duration of a pitch to own the data science / algorithmic building block of the feature.
  • Understand the business needs of our analysts and Product Managers, and translate them into an algorithmic methodology or a statistical learning model.
  • Select, adapt or design the right algorithm, including when the answer isn't an off-the-shelf model: heuristics, statistical methods, graph algorithms, anomaly detection, and so on.
  • Define the evaluation metrics and demonstrate that the solution genuinely answers the need, at our scale.

Ship it and keep it running (MLOps hat)

  • Deploy your algorithms to production for the long run, within a quality assurance process: automated testing, continuous integration, code review.
  • Industrialize the model lifecycle: packaging, reproducibility, versioning, retraining, monitoring and drift tracking.
  • Propose innovative solutions to ensure the resilience and performance of our processing under heavy load.
  • Empower your colleagues by providing the tools they need to leverage high-quality data independently.
  • Bring a critical eye and contribute to the team's growth (knowledge sharing, mentoring).

📍 The position is ideally based in Paris, or can be based in Rennes, with up to 3 remote days per week.

Your profile:

🤩 We are excited to meet you if :

  • You hold a Master's-level degree or above (MSc, engineering school, PhD) and have 3 to 5 years of professional experience combining data science and software development — or a data engineering background with a genuine appetite for algorithms.
  • You are proficient in Python and its scientific ecosystem: pandas, scikit-learn, as well as SQL.
  • You have strong skills in algorithms, complexity classes, optimization, and machine learning: you can reason about an algorithm before implementing it, and estimate what it will cost at scale.
  • You are an engineer, not just a prototyper: you write tested, reviewed, maintainable code, and you are comfortable with continuous integration and software engineering best practices.
  • You are a proactive "doer": autonomous and mature, you take ownership of your subjects rather than waiting for instructions.
  • You are driven by efficiency and resilience, capable of building systems that stay performant under heavy loads.
  • You are deeply curious about new trends in the data ecosystem and about technological change.
  • You write and speak English fluently.

🚀 Bonus point:

  • You have experience in cybersecurity
  • You are comfortable with Spark (PySpark).
  • You hold a PhD in computer science.

👀 Are you interested in this job but feel you haven't ticked all the boxes? Don't hesitate to apply, and tell us in the cover letter section why we absolutely must meet!

Recruitment Process:

📝 Here's what's in store for you if you apply :

  • HR Interview with Clémentine, Talent Acquisition Manager (30')
  • Tech & Culture Fit with Sylvain, Data Ops, and Gildas, Head of Data (45')
  • Technical Interview with Gildas and/or Sylvain (~2h, on site)
  • Interview with Georges, CTO (60')

Our process usually takes about 3 weeks, depending on availability. It includes reference calls. The program: discussions rather than trick questions! These discussions will help you understand how Sekoia works and what it stands for. But they are also (and above all) an opportunity for you to tell us about your career path and your expectations for your next job!

⭐ Sekoia is an equal opportunity employer for any minority, disability, gender identity or sexual orientation. We are committed to hiring and supporting diverse teams of people from all backgrounds, experiences, and perspectives.