Mid/Senior Data Scientist (Incogni)

TL;DR

Mid/Senior Data Scientist (Incogni) (NLP/LLM): Designing, building, and productionizing NLP-heavy machine learning systems for text classification, entity extraction, semantic similarity, and LLM-based workflows with an accent on end-to-end model ownership and pragmatic evaluation. Focus on translating ambiguous business problems into data-driven solutions, writing production-quality Python/SQL pipelines, and communicating trade-offs and outcomes to technical and non-technical stakeholders.

Location: Office with the possibility of up to two remote days per week; WFA policy allows working from almost anywhere in the world.

Salary: 3500-6800 EUR/month (gross), depending on skills and experience.

Company

hirify.global builds data protection and cybersecurity products, including Incogni.

What you will do

• Design, build, and productionize NLP-heavy ML systems (text classification, entity extraction, semantic similarity, and LLM-based workflows).
• Write clean, efficient, testable Python code for data pipelines, feature engineering, modeling, and evaluation.
• Own models end to end: problem framing, data exploration, model selection, validation, deployment, and iteration.
• Collaborate with product and engineering teams to turn ambiguous problems into concrete, data-driven solutions.
• Evaluate and apply modern NLP approaches, from classical methods to transformer-based and generative models, with a focus on impact.
• Communicate findings clearly to technical and non-technical stakeholders, focusing on decisions, trade-offs, and outcomes.

Requirements

• Proven applied data science / machine learning experience with a track record of delivering models to production.
• Strong NLP background with hands-on experience in text modeling, embeddings, transformers, and LLM-based systems.
• Advanced Python skills for production-quality code.
• Solid SQL skills and experience working with large, imperfect real-world datasets.
• Strong ML fundamentals, model evaluation, and understanding of common failure modes.
• Experience working in modern engineering environments (code reviews, testing, version control, CI/CD).

Culture & Benefits

• Time dedicated to learning, conferences, online learning platforms, and books.
• Health and wellness support, including health insurance and regular mental health checks.
• Choice of technical equipment and tools.
• Community and celebrations, including yearly workation and Friday get-togethers.
• Work-life balance with office work encouraged and up to two remote days per week; WFA policy allows working from almost anywhere.
• Additional vacation days depending on tenure and premium hirify.global accounts for you and your family.

Hiring process

• Technical task or interview.
• Meet your team.
• Next steps after the interview stage.