Data Scientist
Content + Source + Freshness • 16 Dec 2025 • 95% confidence
Offer value
Strong potential for career development in data science with a reputable organization, attractive project scope, and mentorship options.
- Engage in impactful projects within FinCrime data
- Collaborate with experienced colleagues
- High potential for skill development and learning
Pros
- Collaboration with R&D teams on cutting-edge projects
- Mentoring opportunities available for career advancement
- Opportunities for continuous learning through certifications
Cons
- Skill requirements may exclude some candidates
- Collaboration in an Agile environment may require flexibility
- Potential pressure to deliver results in a fast-paced setting
Who it's for
Mid-level • On-site/Hybrid
Good fit
- Mid-level data scientists seeking growth
- Professionals with a passion for data and AI
- Individuals eager to mentor and collaborate
Not recommended for
- Entry-level job seekers without experience
- Those lacking technical research capabilities
- Candidates uninterested in teamwork or Agile practices
Motivation fit
Key skills
About the job
• Be part of the Data Science (R&D) team and take data throughout its full lifecycle - research, exploration, preprocessing, development, integration and implementation
• Engage in brainstorming sessions and develop prototypes or proofs of concept that utilize Data Science methods to tackle FinCrime-related challenges
• Collaborate with other departments and clients to understand processes and come up with tailored solutions
• Create automation solutions based on AI agents, Generative AI models, Machine Learning techniques
• Contribute to the development of data science products from technical perspective (application backend, data pipelines) and from sales perspective (pricing, solution architectures, visual representation of the concepts, key value drivers)
• Support junior and mid-level team members through mentoring and technical assistance
• Participate in training, certifications, and conferences (also as a speaker, if you wish)
• Work in an Agile environment alongside backend/frontend/low-code developers, DevOps, and business analysts.
Requirements
- Minimum of 1 year of experience in data science or research & development
- University degree (preferred in Statistics, Econometrics, Mathematics or Computer Science)
- Proficient knowledge in Python programming language
- Familiarity with several key Data Science and Machine Learning packages (e.g., pandas, polars, scikit-learn, Keras, PyTorch, LightGBM)
- Knowledge of Generative AI concepts (e.g. prompt engineering, RAG, AI agents)
- Excellent written & spoken English
- Creative and critical thinking skills
- Curiosity and eagerness to learn about multiple business processes and disciplines
- Nice to have: Knowledge and experience in relational databases (SQL, data warehouse)
- Ability to create simple proof of concept applications in Python (Streamilt, Poetry)
- Interest in solving problems and addressing business challenges with Data and AI.
- Experience in Generative AI-based tools (langchain, langgraph, Vertex AI, Azure OpenAI, or similar technologies) or
- Experience in MLOps/DevOps technologies (Docker, Kubernetes, REST API, CI/CD, Linux) or
- Experience in Cloud solutions (Azure, AWS or GCP preferred).
🔍 ATS Optimization Keywords
Below are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively — a feature exclusive to JobTailor job listings.
Hard Skills
- Python
- Data Science
- Machine Learning
- Generative AI
- pandas
- polars
- scikit-learn
- Keras
- PyTorch
- LightGBM
Soft Skills
- creative thinking
- critical thinking
- curiosity
- eagerness to learn
- mentoring
- collaboration
- problem-solving
- communication
- presentation skills
- brainstorming
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