Senior Data Science Consultant – Econometrics specialist

Epam
Manchester
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Science Consultant - Hybrid Analytics

Senior Data Science Consultant - Hybrid Analytics

frog - Senior Consultant - Data Science (Customer Data)

Hybrid Data Science Consultant: Advanced Analytics

Senior Data Scientist & Consultant: Drive Real Impact

Senior Data Scientist & Consultant - Drive Client Impact

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.