Data & AI Junior Consultant

About the position 

We’re looking for an early-career Data Scientist / ML Engineer to help us design and ship practical, data-driven ML and GenAI prototypes. If you have strong fundamentals, hands-on projects or internships, and a passion for building with LLMs, this role is a great way to accelerate your growth while contributing to real product impact. 

We offer: 

• Strong opportunities for professional and career growth 

• A stable work environment that supports long-term planning 

• Competitive compensation and benefits 

• The chance to work with high-profile clients across Europe 

• Excellent career development opportunities 

• Mentorship, training, and clear development paths 

• Modern tooling and a cloud-first stack 

Responsibilities: 

• Clean, analyze, and prepare datasets; perform EDA and build baseline models 

• Implement feature engineering; run model evaluation and simple A/B tests 

• Develop GenAI and Agentic AI prototypes using LLM APIs and agent frameworks (prompting, embeddings, tool/function calling, basic RAG) 

• Design and implement agent workflows: planning/execution loops, memory, tool integrations (APIs, databases), and multi-step/multi-agent orchestration 

• Evaluate agent performance and reliability; define success metrics, add guardrails/fallbacks, and optimize for cost/latency 

• Collaborate with engineers and analysts on data pipelines and dashboards 

Requirements: 
 

• 0 - 2 years of relevant experience (internships and projects count) 

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Math, Engineering, or equivalent experience 

• Willingness to learn fast, build usable ML/GenAI solutions, and grow with a supportive team 

• Python: pandas, numpy, scikit-learn; basic scripting and unit testing 

• SQL: joins, window functions, performance basics 

• ML/DS: supervised learning, cross-validation, model metrics, handling missing/imbalanced data 

• Visualization: Matplotlib/Seaborn/Plotly; clear storytelling with charts 

• GenAI: experience with LLM APIs (e.g., OpenAI/Anthropic), prompts, embeddings; build simple RAG workflows 

• Agentic AI: experience with agent frameworks and patterns (e.g., LangChain Agents/LangGraph, OpenAI Assistants, CrewAI, AutoGen); tool/function calling, planning loops, memory, multi-agent coordination; guardrails and evaluation best practices 

• Tools: Git, notebooks, MLflow or Weights & Biases (basic usage); familiarity with LangChain/LangGraph or similar; tracing/observability for agent pipelines (e.g., LangSmith, OpenTelemetry) 

• Cloud basics: familiarity with AWS/GCP/Azure services; using Docker locally 

• Statistics fundamentals: hypothesis testing, confidence intervals, experiment design basics 

• Communication: clear writing, documenting, and presenting results 

Nice to have: 

• PyTorch or TensorFlow; LoRA/PEFT familiarity 

• Vector databases (FAISS, Pinecone, Weaviate); Elasticsearch/OpenSearch basics 

• Data warehousing (Snowflake/BigQuery/Redshift); dbt basics 

• Orchestration (Airflow/Dagster) and simple CI/CD 

• BI tools (Looker/Tableau/Power BI) 

• Portfolio: GitHub, Kaggle, blogs, or open-source contributions 

• Previous consulting experience 
   
   

If you meet the qualifications listed above and are eager to advance your career in our exceptional work environment, we encourage you to submit your application by 24.12.2025. 

We are for all. Through our strategy, we are focused on fostering a culture of belonging and equity where a diverse community of solvers can thrive and feel like they truly belong. 

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