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- Tasks: Lead the design and deployment of cutting-edge ML solutions for diverse industries.
- Company: Join EPAM Systems, a global leader in digital transformation and data science.
- Benefits: Enjoy perks like private medical insurance, employee stock purchase plans, and free lunches.
- Why this job: Make a real impact by solving complex challenges with innovative ML technologies.
- Qualifications: Bachelor’s or Master’s in relevant fields; experience in data science and ML engineering required.
- Other info: Opportunities for professional development with access to over 22,000 courses.
The predicted salary is between 48000 - 72000 £ per year.
Principal Data Science & ML Engineering Consultant Join to apply for the Principal Data Science & ML Engineering Consultant role at EPAM SystemsPrincipal Data Science & ML Engineering Consultant 2 days ago Be among the first 25 applicantsJoin to apply for the Principal Data Science & ML Engineering Consultant role at EPAM SystemsAs 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.ResponsibilitiesCollaborate with clients to define their data science and ML strategies, ensuring alignment with business objectives and technical feasibilityLead the design, development, deployment and maintenance of ML models, emphasizing MLOps best practices for scalability and reliabilityDesign and implement data pipelines to process, transform and prepare data for ML workflowsMonitor, evaluate and improve model performance, addressing issues like data drift, model drift and latency in production environmentsBuild CI/CD pipelines for seamless integration of ML models into production systemsWork with cross-functional teams, including data engineers, software developers and business stakeholders, to ensure the successful implementation of ML solutionsImplement AI governance frameworks, ensuring compliance with ethical practices and industry regulationsStay at the forefront of industry trends, emerging ML technologies and innovative tools to continually enhance service offeringsTranslate complex ML concepts into actionable insights and technical roadmaps for stakeholders at various levelsContribute to client-facing activities, including presentations, workshops and responses to RFPs/RFIsRequirementsBachelor\’s or Master\’s degree in Data Science, Statistics, Computer Science, Software Engineering or related fields. A Ph.D. is an advantageExtensive experience in data science, ML engineering or related roles. Experience in leading teams on projects in not required but would be valuedDeep understanding of ML lifecycle management, including feature engineering, model selection, hyperparameter tuning, model validation, model evaluation and deployment for inferenceHands-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 TensorRTProficiency 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 modelsFamiliarity 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 stakeholdersExperience in developing AI applications using large language models (LLMs) and Retrieval-Augmented Generation (RAG) systems (via LangChain, LlamaIndex or custom API-driven approaches)We offerEPAM Employee Stock Purchase Plan (ESPP)Protection benefits including life assurance, income protection and critical illness coverPrivate medical insurance and dental careEmployee Assistance ProgramCyclescheme, Techscheme and season ticket loansVarious perks such as free Wednesday lunch in-office, on-site massages and regular social eventsLearning and development opportunities including in-house training and coaching, professional certifications, over 22,000 courses on LinkedIn Learning Solutions and much moreIf otherwise eligible, participation in the discretionary annual bonus programIf 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 requirementsSeniority level Seniority level DirectorEmployment type Employment type Full-timeJob function Job function Business Development, Information Technology, and EngineeringIndustries Software Development and IT Services and IT ConsultingReferrals increase your chances of interviewing at EPAM Systems by 2xGet notified about new Principal jobs in London, England, United Kingdom .London, England, United Kingdom 17 hours agoLondon, England, United Kingdom 2 months agoSevenoaks, England, United Kingdom 1 month agoLondon, England, United Kingdom 1 week agoHead of Recruitment and Retention Communications London, England, United Kingdom 2 weeks agoLondon, England, United Kingdom 1 week agoLondon, England, United Kingdom 2 months agoLondon, England, United Kingdom 6 days agoLondon, England, United Kingdom 1 week agoHead of People Function Portfolio Management Office London, England, United Kingdom 2 weeks agoVice President, Software Development – Global London, England, United Kingdom 3 days agoLondon, England, United Kingdom 20 hours agoPrivate Equity (LBO, Growth) Principal / Director of Investments London, England, United Kingdom £59,999.00-£60,000.00 14 hours agoLondon, England, United Kingdom 2 weeks agoLondon, England, United Kingdom 1 month agoLondon, England, United Kingdom 1 day agoFeltham, England, United Kingdom 2 weeks agoLondon, England, United Kingdom 6 days agoLondon, England, United Kingdom 1 week agoLondon, England, United Kingdom 1 week agoHead of Facilities Projects, Europe, Middle East & Africa London, England, United Kingdom 4 days agoLondon, England, United Kingdom 1 month agoLondon, England, United Kingdom 2 weeks agoLondon, England, United Kingdom 23 hours agoHead of Education and Student Experience We\’re unlocking community knowledge in a new way. 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Principal Data Science & ML Engineering Consultant employer: EPAM Systems
Contact Detail:
EPAM Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Science & ML Engineering Consultant
✨Tip Number 1
Network with professionals in the data science and ML engineering fields. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and learn about the latest trends. This can help you gain insights into what EPAM Systems is looking for in candidates.
✨Tip Number 2
Showcase your hands-on experience with deploying ML models at scale. If you've worked with platforms like AWS SageMaker or Azure ML, be prepared to discuss specific projects where you optimised model performance. This practical knowledge is crucial for the role.
✨Tip Number 3
Familiarise yourself with MLOps tools and practices. Understanding how to implement CI/CD pipelines and manage model lifecycle will set you apart. Consider sharing examples of how you've used tools like MLFlow or Docker in your previous work.
✨Tip Number 4
Prepare to discuss your approach to translating complex ML concepts into actionable insights. Being able to communicate effectively with both technical and non-technical stakeholders is key for this role, so think of examples where you've successfully done this in the past.
We think you need these skills to ace Principal Data Science & ML Engineering Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and ML engineering. Focus on specific projects where you've built scalable ML solutions or optimised model performance, as these are key aspects of the role.
Craft a Compelling Cover Letter: In your cover letter, emphasise your understanding of the ML lifecycle management and your hands-on expertise with tools like AWS SageMaker or Azure ML. Mention how your skills align with the responsibilities outlined in the job description.
Showcase Technical Skills: Clearly list your proficiency in programming languages and frameworks such as Python, PyTorch, and TensorFlow. Provide examples of how you've used these technologies in past roles to solve real-world challenges.
Prepare for Interviews: Be ready to discuss your experience with MLOps tools and cloud platforms. Prepare to explain complex ML concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
How to prepare for a job interview at EPAM Systems
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with ML frameworks like TensorFlow and PyTorch. Highlight specific projects where you've deployed models at scale, and be ready to explain the challenges you faced and how you overcame them.
✨Understand MLOps Best Practices
Familiarise yourself with MLOps tools and practices, as this role emphasises scalability and reliability. Be ready to discuss how you've implemented CI/CD pipelines and managed model performance in production environments.
✨Communicate Complex Concepts Clearly
Since you'll be bridging the gap between technical and non-technical stakeholders, practice explaining complex ML concepts in simple terms. Prepare examples of how you've successfully communicated technical information in past roles.
✨Stay Updated on Industry Trends
Research the latest trends in data science and ML technologies. Being knowledgeable about emerging tools and methodologies will demonstrate your commitment to continuous learning and innovation, which is crucial for this role.
