Senior Data Scientist / Tech Lead

Quick Facts

• Role: Senior Data Scientist / Tech Lead

• Focus: Lead scalable Machine Learning and GenAI projects, from architecture to production

Description

Lead the development, implementation, and validation of Machine Learning and GenAI solutions, including an AI optimization engine for airport operations and AWS-powered LLM recommendation systems. You will design AI architectures, translate client business problems into data science tasks, and oversee data pipelines with standards for data quality and security. Work closely with Data Engineering and Software Engineering teams, present recommendations to stakeholders, and manage delivery within Agile/Scrum.

Responsibilities

• Lead development, implementation, and validation of Machine Learning solutions

• Design AI solution architectures aligned with complex business goals

• Research and select tools, technologies, and AI solutions to meet requirements

• Translate business problems into data science problems

• Architect and oversee data pipelines and workflows for data quality and security

• Coordinate with Data Engineering and Software Engineering to build AI applications

• Present findings and recommendations clearly to stakeholders

• Prioritize and control tasks in an Agile/Scrum framework for timely delivery

Requirements

• 6+ years of commercial experience designing and implementing scalable AI solutions (ML, predictive modeling, optimization, NLP, computer vision, GenAI, LLMs, deep learning)

• Ability to develop ML algorithms from scratch through production deployment

• Strong Python skills (clean code, OOP) and ML libraries (Scikit-Learn, PyTorch or TensorFlow)

• Experience deploying in cloud environments (AWS or Azure)

• Knowledge of LLMs (AI agents, semantic search, prompt engineering, multimodal embeddings, RAG)

• C1-level English proficiency

• Strong communication and consulting experience with direct client interaction

• Experience with SQL and NoSQL databases (e.g., MongoDB, Snowflake, Databricks)

• Knowledge of CI/CD principles (GitHub, GitHub Actions)

• Familiarity with MLOps practices, Kubernetes, and Docker

• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field

• Plus: Big Data experience (Spark, Hadoop, Kafka)

Benefits

• Supportive AI & Big Data team and work with global enterprises and startups

• Flexible work arrangements (remote or modern offices/coworking spaces)

• Career growth via knowledge sharing, language classes, and sponsored training/conferences (incl. Databricks and Anthropic partnership)

• Team-building events and integration budget

• Medical and sports packages, eye care, and well-being support (incl. psychotherapy and coaching)

• Full work equipment provided (e.g., laptop)

• Opportunity to boost your personal brand via conferences and community activities

• Smooth onboarding with a dedicated buddy in an autonomous culture