Senior Data Scientist – AdTech & Healthcare (f/m/x)

Sii Poland; Kraków; Presencial; PLN 180.000 - 320.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Great Place to Work

Solid financial situation

Contracts with the biggest brands

Centre of internal trainings

Many experts you can learn from

Open and accessible management team

Profit sharing

Passion Sponsorship program

Regular integration events and trips

Comfortable and well-equipped offices

MySii app

Medical care

Descripción de la vacante

Sii Poland is seeking a senior ML engineer to design and implement probabilistic methods for entity linking and predictive modeling on large healthcare datasets. You’ll train production-grade models, own data pipelines, and optimize performance for scale. The role combines research with practical deployment across analytics platforms, delivering measurable business value.

Join a team of experts, work in a modern office in Kraków, and contribute to AI-powered health marketing solutions.

Formación

• Minimum 5 years of experience in training and monitoring ML models for production use.
• Experience with data and ML engineering, including ML-facing ETL processes over very large datasets and data-quality monitoring.
• Expertise in Python data-science and ML libraries like scikit-learn, PyTorch, LightGBM, Splink, spaCy, and Hugging Face
• Practical experience in probabilistic methods for entity linking, matching, imputation, scoring, and evaluation
• Strong command of SQL for distributed warehouses such as Snowflake, BigQuery, or Databricks
• Advanced level of English

Responsabilidades

• Measuring existing model performance and finding ways to improve it
• Owning the design of the new methodology and training the next-gen model for increased predictive power, sample efficiency, and scalability to large datasets
• Extracting unique entities and sparse attributes from heterogeneous sources – both structured and unstructured
• Designing and implementing probabilistic entity linking & matching across multiple large healthcare datasets
• Exploring graph technologies and graph theory
• Building and owning an analytics data store, evaluation, and monitoring pipelines

Conocimientos

ML model production training

Python data-science

Scikit-learn

PyTorch

LightGBM

SpaCy

Hugging Face

SQL for data warehouses

English proficiency

Probabilistic methods

Herramientas

Snowflake

BigQuery

Databricks

Neo4j

Amazon Neptune

Stardog

Descripción del empleo

Tired of building yet another chatbot POC? Do you want to train ML models that bring real monetary value and run at a billion-scale? Do you feel like introducing a brand-new probabilistic methodology for a real-world problem?
We build the AI-powered operating system for healthcare marketing - programmatic advertising, data intelligence, patient affordability and AI-enabled engagement for the life sciences industry.
We are looking for a person who knows how to design and implement statistical methods to extract signals from large, messy, real-world datasets and use them for prediction. Everything we build on top of that, from audience reach to speciality insight to measurement, is only as good as your layer.
Your tasks

• Measuring existing model performance and finding ways to improve it
• Owning the design of the new methodology and training the next-gen model for increased predictive power, sample efficiency, and scalability to large datasets
• Extracting unique entities and sparse attributes from heterogeneous sources – both structured and unstructured
• Designing and implementing probabilistic entity linking & matching across multiple large healthcare datasets
• Exploring graph technologies and graph theory
• Building and owning an analytics data store, evaluation, and monitoring pipelines
  

Requirements

• Minimum 5 years of experience in training and monitoring ML models for production use
• Experience with data and ML engineering, including ML-facing ETL processes over very large datasets and data-quality monitoring
• Expertise in Python data-science and ML libraries like scikit-learn, PyTorch, LightGBM, Splink, spaCy, and Hugging Face
• Practical experience in probabilistic methods for entity linking, matching, imputation, scoring, and evaluation
• Strong command of SQL for distributed warehouses such as Snowflake, BigQuery, or Databricks
• Advanced level of English
  

Nice to have

• Experience with graph technologies such as Neo4j, Amazon Neptune, Stardog, or similar platforms
• Familiarity with Graph Machine Learning concepts, including community detection, Graph Neural Networks (GNNs), and graph embeddings
• Exposure to AI-powered development tools such as Cursor AI, Claude Code, or equivalent solutions
• A proactive mindset with a willingness to take ownership of deliverables and contribute to product direction
  

Job no. JOB-AV29D
Sii ensures that all hiring decisions are made solely on the basis of qualifications and competence. We are committed to equal and fair treatment of all, regardless of legally protected characteristics. At Sii, we promote a diverse and inclusive work environment, in full compliance with applicable anti-discrimination laws.
Benefits For You

• Great Place to Work
• Solid financial situation
• Contracts with the biggest brands
• Centre of internal trainings
• Many experts you can learn from
• Open and accessible management team
• Profit sharing
• Passion Sponsorship program
• Regular integration events and trips
• Comfortable and well-equipped offices
• MySii app
• Medical care