Senior AI & Data Scientist

Tyche Consulting AB; Solna kommun; Hybrid; SEK 70,000 - 90,000; Full time

Benefits offered by this job

Attractive bonus package

Flexible working environment

Structured professional development opportunities

Job summary

Tyche Consulting AB is looking for a Senior AI & Data Scientist in Stockholm to lead the AI lifecycle from research to deployment. You will design advanced Machine Learning models and collaborate with stakeholders to turn complex data into competitive advantages.

Ideal candidates have substantial experience in Data Science and AI, with strong programming skills in Python and SQL. The company promotes a flexible work environment fostering a healthy work-life balance.

Qualifications

• 6–8+ years of professional experience in Data Science, Machine Learning, or AI Engineering.
• Exceptional programming skills in Python and strong proficiency in SQL.
• Deep understanding of Machine Learning algorithms and predictive analytics.

Responsibilities

• Design and deploy advanced Machine Learning models for business optimization.
• Collaborate with stakeholders to turn complex data into competitive advantages.
• Build next-generation LLM-based applications utilizing RAG and Agentic AI.

Skills

Machine Learning

Python programming

Data Science

SQL proficiency

Cloud platforms (GCP, AWS, Azure)

Data Engineering

Education

Degree in Computer Science or related field

Tools

Docker

Kubernetes

Databricks

Job description

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.

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)

• 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.