Machine Learning Data Scientist

About our client

A global data and analytics company with more than four decades in the field. Offices in North America, Europe and Asia-Pacific, and large enterprise customers who rely on its platforms for advanced analytics, data science and cloud analytics.

The European tech hub delivers data and analytics projects, mostly in finance and other regulated industries.

▸ Why This Role Exists Now

A data project for a Nordic banking customer is starting, and the delivery team is adding a data scientist for it. You join at the start, so hands-on experience taking ML to production in agile teams counts most.

Job description

▸ Role / Mission

You're the data scientist in the delivery team. A business problem comes in, you turn it into a machine learning solution, build it in Python on large datasets in Teradata Vantage, and hand it over ready for production.

Typical use cases on banking projects like this one: fraud and anomaly detection in transactions, credit risk scoring, churn prediction and customer segmentation.

By the end of the contract, the use cases you started as experiments run as deployed solutions.

▸ Key Responsibilities

- Turn business problems into data science use cases and agree the approach with the business
- Build and test ML models, from first experiment to a production-ready version
- Deploy them, using feature stores to develop and serve models
- Use generative AI (LLMs, transformers) where the use case calls for it
- Present results to executives, business owners and engineers
- Work with data engineers, analysts and domain experts on the delivery

▸ What This Role Is NOT

- Not a research role. The models are meant to reach production.
- Not a strategy-on-slides role. You help shape the approach, and you also write the code.

▸ Operating Model

- Remote. In the initial phase of the project, 1–2 days a week on-site in Prague for onboarding.
- Working language is English.
- You join a team of specialists on the project, working in an agile way, and report to the Head of Delivery.

Requirements

▸ What Matters Most

- 2+ years in data science or applied machine learning, delivered in agile teams, with a business result you can point to
- Advanced Python for data science – Pandas, scikit-learn, NumPy
- Strong SQL on large datasets – Teradata Vantage is a big plus
- Fluent English, and the ability to explain methods and results to technical and non-technical people

Seniority is not a hard filter. If you've done the work, we want to hear from you. Motivation counts as much as the tick-list.

▸ Nice to Have

- Banking, finance or another regulated industry
- Time series or anomaly detection
- Cloud (AWS, Azure, GCP), MLOps, CI/CD for ML, Docker, APIs
- Data visualisation (Power BI, Tableau)

Offer & Terms

- Rate: CZK 120,000–160,000 per month
- B2B contract, starting ASAP, six months, with possible extension
- 4–8 hours a day; part-time is possible, with flexibility on both sides

More information

▸ Interested? Reach out

A link to your LinkedIn is enough – no CV needed. If your profile isn't quite up to date and you don't have the time or energy to fix it, just send a few lines about your 2–3 most recent projects instead.

▸ What Happens Next

- First, a quick call with us – no recruiter fluff, straight to the point.
- Then 1–2 classic rounds with the client – expertise & fit.
- We'll get back to you at every step of the process, either way. Sometimes it takes a bit longer, and we're not perfect either, but we know you don't need more ghosting.

A dedicated consultant handles this position.
Recruitment quality is personally guaranteed by SITEQ's founder, backed by his own long-standing IT background & 500+ placements.

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Open only to candidates based in the Czech Republic and eligible to work in the EU without visa sponsorship.

Other open positions: siteq.cz/en/jobs.
Thank you!