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Senior Data Scientist (Customer-focused / applied ML) | Big-data company [25-30k PLN B2B]

Bee Talents Wrocław Today

data

Who are we?

We're Bee Talents, an IT recruitment agency that has been helping clients from all around the world in building their technical teams since 2015. Today, we would like to invite you to participate in the recruitment process for one of our clients, focused on big-data topic.

This big-data company has nearly a decade of experience in the international market (mainly in Europe). Now, we’re looking for a person to their Polish department. They're motivated by real-world impact and by building high-quality, production-ready systems using LLMs and NLP to generate meaningful insights from complex data.

Now, we’re looking together for a Senior Data Scientist (Customer-focused / applied ML) who will join the Polish team and will work both on data as a specialist, but won’t be afraid of supporting Product Managers in talking with clients and offering them the best solution tailored for their needs!

What they can offer you:

🎯 Role: Senior Data Scientist (Customer-focused / applied ML)

💰 Salary: 25-30k PLN net on the invoice on B2B/month + % of equity!

⏱ Working hours: flexible between 6:00-18:00

👩‍💻 Working mode: hybrid/remote (1-2 days in the office in Wroclaw)

🇬🇧 Speaking language: Polish & English on a communicative+ level as we work in both - Polish and multinational environment.

The biggest challenge in this role:

You’ll own problem-framing -> modelling -> learning strategy -> production impact for a specific data domain, in close partnership with Product Management.

Your responsibilities:

Customer-driven classification - designing, training, and evolving high-precision text classifiers over noisy, real-world data sources. Success is measured by downstream customer outcomes, not just offline metrics.

Working under ambiguity - with labels shaped by human judgment, business context, and evolving criteria. You’ll reason about disagreement, uncertainty, and “good enough” definitions rather than assuming a single ground truth.

Using LLMs as tools, not magic - working with LLMs where they actually help: weak supervision, zero-/few-shot classification, feature extraction, assisted labeling, or synthetic data generation - with a clear understanding of failure modes and bias.

Active learning & data strategy - deciding what to label next and why. Building active learning loops that maximize information gain while minimizing labeling effort and cost.

Spec-driven, agent-friendly development - co-shaping explicit, testable specifications with teams focused on Product Management and Engineering, taking a leading role in defining learning objectives, labels, and model behavior so that engineering teams and their AI-assisted workflows can reliably execute.

End-to-end ownership - taking the responsibility of business value and experimentation through deployment and monitoring. You’ll collaborate closely with the Engineering Team building the platform, while operations run and monitor the production pipelines - your role is to ensure models, specifications, and learning strategies align cleanly across both.

Decisions are expected to be pragmatic and iterative - clarity and momentum matter more than theoretical completeness.

What you’ll need?

Min. 5 years of experience in building and deploying classifiers, with at least 3 years on noisy, real-world text and understanding trade-offs in feature engineering, modeling choices, and evaluation under uncertainty (Strong ML/ NLP foundation; not Computer Vision).

Data science engineering mind - with a strong experience in Python, cloud, production-ready code and models beyond notebooks - taking care about QA, monitoring, and long-term behavior at the same time.

Hands-on experience in designing data pipelines and transforming unstructured data into actionable insights.

Practical LLM experience - using LLMs in production or near-production workflows and know when they help - and when they absolutely don’t.

Customer-oriented mindset - asking “what problem are we really solving for the customer?” before “how do we model this?” - with the comfort of talking directly to stakeholders and shaping definitions.

B2/C1 levels of both Polish and English while speaking and writing with the team and clients!

Nice to haves: experience in life sciences; familiarity with scikit-learn and pandas.

What you’ll get?

Salary of 25-30k PLN/month B2B.

Growth - % of equity, coaching to grow your technical influence and impact.

High autonomy - latitude to choose approaches, influence architecture, and shape the product and company direction.

Flexibility with working via hybrid mode.

Nice culture - working on OKRs, with transparent and async-friendly communication plus bias-to-action mindset.

Sounds interesting? Let’s talk! :)

PS There will be 4 stages of the recruitment process (Recruiter screening, Hiring Manager meeting, Technical meeting, Final/Culture fit meeting).

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