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Senior Data Science Consultant – Econometrics specialist

Epam
London
1 year ago
Applications closed

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Senior Data Science Consultant – Econometrics specialist

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Senior Data Scientist Econometrics & Advanced Attribution

Contract Senior Data Scientist – Econometrics & Advanced Attribution...

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
National AI Awards 2025

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