Data Scientist

Konecta; Paris; Sur place; EUR 50 000 - 80 000; Plein temps

Résumé du poste

A leading global service provider is seeking a Data Scientist in Advisory & Professional Services to design and implement generative AI solutions. The ideal candidate will have experience in data science, strong technical skills, and a passion for creating business value through data. This full-time role offers an opportunity to work on innovative projects in a collaborative environment.

Qualifications

• 3–5 years of experience in data science or applied machine learning.
• Hands-on experience with LLM APIs and prompt engineering.
• Ability to communicate with both technical and non-technical audiences.

Responsabilités

• Assist in designing and building Gen AI prototypes using LLMs.
• Support feature engineering, evaluation, and testing of models.
• Collaborate with squads to refine agent behavior and tool integrations.

Connaissances

Python

Machine Learning

Data Science

Prompt Engineering

REST APIs

Team Collaboration

Outils

LangChain

Hugging Face

scikit-learn

Pandas

Jupyter

MLflow

DVC

Azure

AWS

GCP

Description du poste

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ABOUT US

Konecta is a leading innovative global service provider in customer management, business process, and digital outsourcing, with 120,000 passionate employees working in 30 languages across 4 continents and 26 countries. Focusing on the unique needs and opportunities of each industry, Konecta offers a full range of end-to-end customer management solutions – including acquisition, retention, customer service, technical support, and collection – all based on a sustainable business model. These services are built on a portfolio of world-class expertise covering customer experience and process management, digital solutions, and cutting-edge technologies. Headquartered in Madrid, Konecta delivers global revenues of €2 billion with more than 500 clients, covering some of the biggest names in telecoms, energy, banking, mobility, retail, and e-commerce.

MISSION OF THE ROLE

The Data Scientist in Advisory & Professional Services plays a key role in designing and implementing generative AI solutions that solve real business problems. Working closely with senior data scientists, consultants, and engineers, this role supports the development of prototypes, PoVs, and client-facing solutions using state-of-the-art AI models, agentic frameworks, and techniques. The ideal candidate combines hands-on technical ability with curiosity and the drive to create business value through data.

RESPONSIBILITIES

Technical Delivery:

• Assist in designing and building Gen AI prototypes using LLMs, embeddings, RAG pipelines, and fine-tuning techniques.
• Develop and test agentic workflows using frameworks like LangChain Agents, CrewAI, AutoGen, or Databricks Mosaic AI.
• Support feature engineering, evaluation, and testing of models in collaboration with architects and engineers.
• Create clean, reusable code and Jupyter notebooks that align with internal quality and documentation standards.
• Participate in client workshops, discovery sessions, and technical validation phases.
• Translate client needs into tractable data science tasks and communicate results clearly.
• Collaborate with squads to refine agent behavior, planning strategies, and tool integrations.
• Support the presentation of prototypes and findings in pre-sales and advisory engagements.

Reusability & Innovation:

• Contribute to internal libraries, prompt collections, evaluation frameworks, and demo environments.
• Help maintain Gen AI accelerator kits and refine them based on project experience.

Governance & Compliance:

• Apply responsible AI principles including explainability, fairness, and auditability in project work.
• Ensure alignment with the AI governance framework, especially regarding EU AI Act and data protection.

REQUIREMENTS

• 3–5 years of experience in data science or applied machine learning, preferably in a consulting or client-facing environment.
• Hands-on experience with LLM APIs, embeddings, vector databases, and prompt engineering.
• Skilled in Python and ML libraries such as LangChain, Hugging Face, scikit-learn, Pandas, and Jupyter.
• Familiarity with MLOps concepts and tools like MLflow, DVC, or cloud-based model deployment (Azure, AWS, GCP).
• Ability to communicate clearly to both technical and non-technical audiences.
• Comfort working with REST APIs, event-driven architectures, and integrating external tools into agent workflows.
• A team player with an appetite for learning, co-creation, and working in multidisciplinary squads.
• Awareness of ethical AI, responsible AI practices, and data privacy guidelines.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Outsourcing and Offshoring Consulting