Principal Data Science & ML Engineering Consultant

As a global leader in digital transformation, we are expanding our Data Practice across Europe to address growing client demand for advanced Data Science and Machine Learning (ML) engineering services. We are seeking a talented and experienced Principal Data Science & ML Engineering Consultant to join our dynamic team. This role emphasizes building scalable, production-ready ML solutions, optimizing model performance and driving technical innovation across diverse industries.

In this position, you will bridge the gap between data science and software engineering, delivering robust data-driven solutions that empower clients to solve real-world challenges and unlock measurable value.

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Responsibilities

Collaborate with clients to define their data science and ML strategies, ensuring alignment with business objectives and technical feasibility
Lead the design, development, deployment and maintenance of ML models, emphasizing MLOps best practices for scalability and reliability
Design and implement data pipelines to process, transform and prepare data for ML workflows
Monitor, evaluate and improve model performance, addressing issues like data drift, model drift and latency in production environments
Build CI/CD pipelines for seamless integration of ML models into production systems
Work with cross-functional teams, including data engineers, software developers and business stakeholders, to ensure the successful implementation of ML solutions
Implement AI governance frameworks, ensuring compliance with ethical practices and industry regulations
Stay at the forefront of industry trends, emerging ML technologies and innovative tools to continually enhance service offerings
Translate complex ML concepts into actionable insights and technical roadmaps for stakeholders at various levels
Contribute to client-facing activities, including presentations, workshops and responses to RFPs/RFIs
Requirements
Bachelors or Masters degree in Data Science, Statistics, Computer Science, Software Engineering or related fields. A Ph.D. is an advantage
Extensive experience in data science, ML engineering or related roles. Experience in leading teams on projects in not required but would be valued
Deep understanding of ML lifecycle management, including feature engineering, model selection, hyperparameter tuning, model validation, model evaluation and deployment for inference
Hands-on expertise in deploying ML models at scale in production environments (via platforms such as AWS SageMaker or Azure ML), and optimising models for efficient inference using formats like ONNX and TensorRT
Proficiency in Python and ML/engineering frameworks such as PyTorch, TensorFlow (including Keras), Hugging Face (Transformers, Datasets) and scikit-learn, etc
Experience with MLOps tools, including MLFlow, workflow orchestrators (Airflow, Metaflow, Perfect or similar), and containerisation (Docker)
Strong knowledge of cloud platforms like Azure, AWS or GCP for deploying and managing ML models
Familiarity with data engineering tools and practices, e.g., distributed computing (e.g., Spark, Ray), cloud-based data platforms (e.g., Databricks) and database management (e.g., SQL)
Strong communication skills, capability to present technical concepts to technical and non-technical stakeholders
Experience in developing AI applications using large language models (LLMs) and Retrieval-Augmented Generation (RAG) systems (via LangChain, LlamaIndex or custom API-driven approaches)
We offer
EPAM Employee Stock Purchase Plan (ESPP)
Protection benefits including life assurance, income protection and critical illness cover
Private medical insurance and dental care
Employee Assistance Program
Competitive group pension plan
Cyclescheme, Techscheme and season ticket loans
Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
Learning and development opportunities including in-house training and coaching, professional certifications, over 22,000 courses on LinkedIn Learning Solutions and much more
If otherwise eligible, participation in the discretionary annual bonus program
If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program
*All benefits and perks are subject to certain eligibility requirements

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