Data Science Principal

What we offer

Interact with our clients on regular basis, to drive their business towards impactful change.

Work in multidisciplinary teams and learn from motivated colleagues.

A chance to take responsibility for your work, develop yourself every day and take full ownership of your career.

Become part of a fast growing international and diverse team.

What you will do 

Manage client interactions and play a key role in building and maintaining client relationships.

Translate business problems to analytics solutions with clear output. Translate analytical output to drive business decisions that create impact.

Provide project management oversight required to meet client expectations.

Responsibilities may include overall project delivery quality, development of presentations, and managing of external relationships.

Function as a sounding board for data and analytics related questions of client business leadership.

Seek compelling opportunities beyond the scope of the current project.

Provide guidance to more junior members of the team, while orchestrating the work of the entire team. Drive growth and development for the members of the team.

What You’ll Bring

+8 years of consulting experience or relevant industry experience, with at least 3+ years at a project lead level.

Master (or Ph.D.) degree in a quantitative field with a focus on data analysis (e.g. econometrics, AI, mathematics, physics, and other exact sciences).

Sharp thinking ability to be able to quickly differentiate major contributors from irrelevant details and to hierarchically structure information residing in the data under analysis.

Robust knowledge of statistical concepts, accompanied by expertise with a set of analytical tools ranging from databases (e.g. SQL, BigQuery, noSQL) to programming languages (e.g. R, Python), and from data visualisation (e.g. Tableau, PowerBI) to machine learning. Understanding data engineering solutions is a plus.

Strong experience in MLOps, including model lifecycle management, CI/CD for ML, monitoring, and scalable deployment of ML pipelines in production environments

Knowledge of CloudOps practices, with expertise in managing scalable, cost-optimized, and resilient data and ML workloads across major cloud platforms (AWS, Azure, or GCP)

Experienced in architecting scalable ML solutions on cloud platforms, leveraging cloud-native services for data pipelines, model deployment, and system reliability

Deep understanding of DevOps principles, including infrastructure as code (IaC), automated testing, containerisation (Docker, Kubernetes), and CI/CD pipelines

Working knowledge of embedding compliance and security in ML systems, including governance, access controls, and regulatory alignment (e.g., GDPR, HIPAA)

Proficient with modern AI tooling and ecosystems, including Hugging Face, Cursor, vector DBs, and productivity tools that accelerate GenAI development

Expertise in GenAI and LLMs, with hands-on experience in RAG solutions and agentic frameworks; capable of leading end-to-end design and deployment of GenAI-driven systems

Proven ability to manage projects with expert team members and to provide inspiring guidance to juniors in the team.

Excellent communication skills, especially to explain complex analytical concepts in non-technical terms to business users.

Professional fluency in English.

In a changing world, diversity and inclusion are core values for team well-being and performance. At Metyis, we want to welcome and retain all talents, regardless of gender, age, origin or sexual orientation, and irrespective of whether or not they are living with a disability, as each of them has their own experience and identity.