Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Science Consultant – Econometrics specialist

Epam
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Senior Consultant, Data Science & AI, Data & Analytics, Belfast, Derry/Londonderry

Senior Consultant, Data Science & AI, Data & Analytics, Belfast, Derry/Londonderry

Senior Data Scientist

Senior Data Engineer

Principal Data Science Consultant - Gen AI Specialist

Description

ABOUT THE ROLE



Are you passionate about Data Science? Do you enjoy working with both technical and business stakeholders to translate vision and designs into sustainable, customer-focused solutions?

Can you communicate efficiently and influence quicker deliveries? If yes, we have new position for a Senior Data Science Consultant. The successful candidate will be a key player in driving the development and implementation of advanced pricing and marketing optimization models. The role involves leveraging deep expertise in Bayesian statistics, causal inference and econometric methods, as well as proficiency in Python, to deliver impactful insights and solutions in the CPG (Consumer Packaged Goods) domain.

Responsibilities

Design and build sophisticated pricing and marketing optimization models using Bayesian, causal inference and econometric approaches Develop optimization models and employ Monte Carlo simulations for robust analysis Lead A/B testing initiatives for accurate measurement and validation of models Analyze large datasets to identify trends, patterns and actionable insights Collaborate with cross-functional teams to understand business needs and provide data-driven solutions Proficiently use Python for model development and ensure models are production-ready Manage the end-to-end process of taking models to production, ensuring scalability and reliability Utilize Azure, Databricks, MLFlow, Airflow and Plotly Dash for efficient model deployment and visualization Apply domain knowledge in CPG pricing and promotion optimization to enhance model accuracy and relevance Work closely with other data scientists, engineers and business stakeholders Mentor junior team members and contribute to the team's knowledge sharing

Requirements

Masters degree or higher in a quantitative field (e.g., Computer Science, Statistics, Physics, Mathematics) Minimum of 5 years of experience in a data science role with a focus on pricing and marketing optimization Proven expertise in Bayesian, causal inference and econometric methods Strong proficiency in Python and experience in taking models to production Experience with cloud computing platforms, preferably Azure and tools such as Databricks, MLFlow Airflow and Plotly Dash

Nice to have

PhD in a relevant field Prior experience in the CPG industry, specifically in pricing and promotion optimization

Our Benefits Include

A competitive group pension plan and protection benefits including life assurance, income protection and critical illness cover Private medical insurance and dental care Cyclescheme, Techscheme and season ticket loans Employee assistance program Great learning and development opportunities, including in-house professional training, career advisory and coaching, sponsored professional certifications, well-being programs, LinkedIn Learning Solutions and much more EPAM Employee Stock Purchase Plan (ESPP) Various perks such as gym discounts, free Wednesday lunch in-office, on-site massages and regular social events Certain benefits and perks may be subject to eligibility requirements and may be available only after you have passed your probationary period

About EPAM

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.