Senior AI & Data Scientist

About the role

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.

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.

Benefits

Additional Information

Location: Stockholm, Sweden (Flexible/Hybrid) Employment Type: Full-time Language: English

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