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For Companies At a Glance
- Tasks: Design and implement advanced pricing and marketing optimisation models using data science techniques.
- Company: EPAM is a leading global provider of digital platform engineering and development services.
- Benefits: Enjoy perks like private medical insurance, gym discounts, and professional development opportunities.
- Why this job: Join a diverse team and make a real impact in the CPG industry with innovative projects.
- Qualifications: Masters degree in a quantitative field and 5+ years of data science experience required.
- Other info: Remote work options available; must have EU work permit.
The predicted salary is between 43200 - 72000 £ per year.
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 a new position for a Senior Data Science Consultant. The successful candidate will play a key role in developing and implementing advanced pricing and marketing optimization models, leveraging expertise in Bayesian statistics, causal inference, econometric methods, and proficiency in Python to deliver impactful insights in the CPG 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 analysis
- Lead A/B testing initiatives for measurement and validation
- Analyze large datasets to identify trends and actionable insights
- Collaborate with cross-functional teams to understand business needs and provide data-driven solutions
- Use Python for model development and ensure models are production-ready
- Manage the end-to-end process of deploying models, ensuring scalability and reliability
- Utilize Azure, Databricks, MLFlow, Airflow, and Plotly Dash for deployment and visualization
- Apply domain knowledge in CPG pricing and promotion to improve model relevance
- Work closely with data scientists, engineers, and stakeholders
- Mentor junior team members and share knowledge
Requirements
- Masters degree or higher in a quantitative field (e.g., Computer Science, Statistics, Physics, Mathematics)
- Minimum 5 years of experience in data science, focusing on pricing and marketing optimization
- Expertise in Bayesian, causal inference, and econometric methods
- Strong proficiency in Python and experience deploying models
- Experience with cloud platforms, preferably Azure, Databricks, MLFlow, Airflow, and Plotly Dash
Nice to Have
- PhD in a relevant field
- Experience in the CPG industry, specifically in pricing and promotion optimization
Benefits
- Group pension plan, life assurance, income protection, and critical illness cover
- Private medical and dental insurance
- Cyclescheme, Techscheme, season ticket loans
- Employee assistance program
- Learning and development opportunities, professional training, certifications, well-being programs, LinkedIn Learning, and more
- EPAM Employee Stock Purchase Plan (ESPP)
- Perks like gym discounts, free lunch, massages, social events
About EPAM
- Leading global provider of digital platform engineering and development services
- Committed to positive impact, inclusive culture, and innovation
- Collaborate with diverse, multinational teams on innovative projects
- Opportunities for learning, growth, and discovering your potential
Senior Data Science Consultant – Econometrics specialist employer: EPAM
Contact Detail:
EPAM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Science Consultant – Econometrics specialist
✨Tip Number 1
Familiarise yourself with the latest trends in econometrics and data science, especially in the context of pricing and marketing optimisation. This will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the CPG industry and attend relevant meetups or webinars. Engaging with others in the field can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Brush up on your Python skills, particularly in relation to model development and deployment. Consider working on personal projects or contributing to open-source projects that showcase your ability to apply econometric methods using Python.
✨Tip Number 4
Prepare to discuss your experience with cloud platforms like Azure and Databricks. Be ready to share specific examples of how you've used these tools in past projects to enhance your candidacy.
We think you need these skills to ace Senior Data Science Consultant – Econometrics specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in pricing and marketing optimisation. Emphasise your expertise in Bayesian statistics, causal inference, and econometric methods, as well as your proficiency in Python.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your ability to work with both technical and business stakeholders. Mention specific projects where you've successfully developed and implemented models, and how they delivered impactful insights.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially your experience with cloud platforms like Azure, Databricks, and MLFlow. Provide examples of how you've used these tools in previous roles to enhance model deployment and visualisation.
Highlight Leadership Experience: If you have experience mentoring junior team members or leading A/B testing initiatives, make sure to include this in your application. Demonstrating leadership skills can set you apart from other candidates.
How to prepare for a job interview at EPAM
✨Showcase Your Technical Skills
Make sure to highlight your expertise in Bayesian statistics, causal inference, and econometric methods during the interview. Be prepared to discuss specific projects where you've applied these skills, especially in pricing and marketing optimisation.
✨Demonstrate Your Problem-Solving Ability
Prepare to discuss how you've tackled complex data challenges in the past. Use examples that illustrate your analytical thinking and ability to derive actionable insights from large datasets, particularly in the CPG domain.
✨Communicate Effectively with Stakeholders
Since the role involves collaboration with both technical and business teams, practice articulating your ideas clearly. Be ready to explain how you can bridge the gap between data science and business needs, ensuring your solutions are customer-focused.
✨Familiarise Yourself with Relevant Tools
Brush up on your knowledge of Azure, Databricks, MLFlow, Airflow, and Plotly Dash. Being able to discuss your experience with these tools will demonstrate your readiness to manage the end-to-end process of deploying models effectively.
