Location: Stockholm, Sweden (Flexible/Hybrid)
Employment Type: Full-time
Language: English
About Us
We are a fast-growing IT consultancy dedicated to delivering cutting-edge expertise to industry-leading clients. Our mission is simple: empower organizations to build scalable, data-driven products that elevate user experience, optimize operations, and unlock business performance through modern AI and advanced analytics.
As we scale, we are looking for a seasoned Senior AI & Data Scientist to join our elite team of experts and help shape the future of our AI offerings.
The Role & Responsibilities
As a Senior AI & Data Scientist, you will own the full AI lifecycle—from initial research and development to deployment and production monitoring. You will collaborate closely with product managers, engineers, and business stakeholders to turn complex data into competitive advantages.
Key Responsibilities:
Model Development: Design and deploy advanced Machine Learning models for business optimization, predictive analytics (forecasting/classification), and recommendation systems.
Generative AI: Build next-generation, LLM-based applications utilizing RAG and Agentic AI architectures.
Data & ML Ops: Design scalable ETL/feature engineering pipelines and build production-ready ML pipelines with CI/CD workflows.
Deployment: Deploy and manage ML models efficiently using Docker and Kubernetes.
Domain Solutions: Develop specialized AI solutions for fraud detection, risk analysis, and customer personalization.
Strategic Impact: Analyze large-scale datasets to generate actionable business insights and actively contribute to our clients' long-term AI strategies.
Required Qualifications
To thrive in this role, you should bring a strong blend of theoretical knowledge and hands-on production experience.
Education: Degree in Computer Science, Computer Engineering, Data Science, or a related quantitative field.
Experience: 6–8+ years of professional experience in Data Science, Machine Learning, or AI Engineering.
Core Tech: Exceptional programming skills in Python and strong proficiency in SQL.
ML/Stats: Deep understanding of Machine Learning algorithms, statistical modeling, and predictive analytics.
Cloud & Infrastructure: Hands-on experience with cloud platforms (GCP, AWS, or Azure) alongside Docker and Kubernetes.
Data Engineering: Experience building production-grade ML pipelines and working with distributed data platforms like Databricks.
Best Practices: Strong version control habits (Git) and experience with CI/CD pipelines.
Soft Skills: Excellent English communication skills, with the ability to translate complex technical concepts for business stakeholders.
Preferred Qualifications (Nice to Have)
Experience with any of the following tools and concepts is considered a distinct advantage:
GenAI Stack: LangChain, LlamaIndex, RAG architectures, and Agentic AI.
MLOps Tools: MLflow, Kubeflow, Airflow, and Feature Stores.
Data Tools: DBT, BigQuery, and real-time data processing frameworks.
Specialized Analytics: A/B testing, customer analytics, and fraud detection.
What We Offer
Compensation: Salary plus a very attractive bonus package based on performance.
Flexibility: A flexible working environment that supports a healthy work-life balance.
Impact: A direct opportunity to shape the AI strategy for major global brands.
Culture: A vibrant, collaborative, and international team environment.
Growth: Structured professional development opportunities and clear paths for long-term career progression.