Staff Applied Scientist (Marketing)

34k - 47k PLN34 000 - 47 000 PLN/ mies./ mies.B2BB2B (netto)

SeniorHybryda·KrakówFull-time·B2B

#471366·Dodano 5 dni temu·1

Źródło: justjoin.it

Aplikuj teraz

Tech Stack / Keywords

Python SQL PyTorch Machine LearningStatisticsExperimental design

Podsumowanie oferty

Shape how Bizee uses AI to improve marketing acquisition, conversion, and customer value. You will turn open-ended questions into experiments, models, and systems, working with Marketing, Product, and Engineering. The role includes training and adapting models with Python, SQL, and PyTorch.

Wymagania

Track record in applied science or machine learning defining problems under uncertainty and taking models from experimentation into sustained business use.
Strong foundations in statistics, machine learning, and experimental design, with depth in causal inference, marketing science, personalization, or optimization. Ability to identify bias, quantify uncertainty, and explain what an experiment establishes.
Hands-on experience developing models for customer behavior or marketing decisions and applying AI to business workflows; ability to choose between predictive models, experimentation, and LLM-based approaches.
Strong Python and SQL skills; experience with PyTorch or an equivalent framework; ability to write tested, maintainable code for reproducible experiments and production collaboration. Use AI tools to accelerate work while verifying generated code and analysis.
Experience with customer, product, or campaign data and the limitations of observational evidence; ability to choose meaningful metrics, build representative evaluation sets, and connect offline results to measured business impact.
Sound judgment about AI reliability and sensitive data, including addressing unsupported outputs, prompt injection, and data exposure, and designing traceable results with appropriate review and fallback behavior.
Autonomy to identify problems when goals or evidence conflict, prioritize experiments, and make practical trade-offs. Clear communication in English and ability to establish methods and decisions that help colleagues work independently.
A master’s or PhD in computer science, machine learning, statistics, or a related discipline, or equivalent experience demonstrating comparable scientific depth and delivery.

Nice to have:

Experience with uplift modeling, recommendation systems, customer lifetime value, retention, or budget optimization.
Experience measuring campaign incrementality, working with advertising platforms, or combining experimental and observational evidence.
Experience with LLM-based personalization or content workflows, including evaluating quality, factual accuracy, and downstream customer outcomes.
Experience operating ML systems in the cloud, or research and open-source contributions demonstrating original thinking and practical impact.

Obowiązki

Partner with Marketing, Product, and Engineering to identify opportunities, use customer and campaign data to test assumptions, and define hypotheses and measures of business success.
Develop models and AI workflows for audience understanding, personalization, recommendations, campaign optimization, and content generation.
Design controlled experiments to measure incremental improvements; use causal methods when randomization is impractical and explain their assumptions.
Train, adapt, and evaluate models for marketing tasks, comparing statistical baselines, predictive models, and LLM-based approaches.
Develop reliable training and evaluation datasets from customer, campaign, and product data; address missing data, bias, and imbalance, prevent leakage, and respect privacy and consent requirements.
Create repeatable evaluations connecting model performance to marketing decisions and customer outcomes. For generative applications, test factual accuracy and failure cases using Bizee examples, expert review, and validated automated checks.
Own scientific outcomes through production and adoption; partner with engineers to deploy and monitor models, diagnose performance changes, and improve latency and cost. Build feedback loops, track data and model versions, and define when to retrain, revise, or retire solutions.
Follow advances in AI and test ideas that could improve Bizee’s products. Explain results and trade-offs, document experiments, and share reusable methods.

Benefity

Stock options.
Annual bonus.
Flexible benefits allowance to spend on what matters to you.
Real ownership and the opportunity to make a visible impact.

Udziały pracownicze

Premie

Bizee

6 aktywnych ofert

Zobacz wszystkie oferty

Aplikuj teraz