At a Glance
- Tasks: Lead AI-driven consumer segmentation projects and drive innovation across markets.
- Company: Join PMI, a forward-thinking company embracing revolutionary change.
- Benefits: Enjoy a dynamic work environment with opportunities for career growth and well-being support.
- Other info: Inclusive culture with networks for diverse backgrounds and a commitment to employee well-being.
- Why this job: Be at the forefront of AI innovation and make a real impact on consumer engagement.
- Qualifications: 7-10 years in ML engineering or data engineering with strong MLOps experience.
The predicted salary is between 75600 - 92400 £ per year.
Be a part of a revolutionary change!
At PMI, we’ve chosen to do something incredible.
With huge change, comes huge opportunity.
So, wherever you join us, you’ll enjoy the freedom to dream up and deliver, better, brighter solutions in a space that allows you to move your career forward in endlessly different directions.
Why Join Us
In this role, you will be at the center of building and scaling AI-driven consumer segmentation capabilities across markets.
You will drive the technical foundation behind advanced analytics and AI solutions, ensuring reliable deployment, strong governance, operational excellence, and business impact.
Working closely with cross-functional stakeholders, you will help shape the future of AI-enabled consumer engagement while driving innovation, scalability, and continuous improvement across the organization.
Role Purpose
Own the delivery, scalability, and performance of AI-driven consumer segmentation and NBA capabilities, acting as the backbone of the AI platform and ensuring efficient deployment across markets.
Key Responsibilities
- Data Science Framework Ownership & Development
- Define data science modeling standards and best practices across training, validation, deployment, and monitoring.
- Ensure models are scalable across markets, reproducible and maintainable, and aligned with PMI architecture and AI standards.
- Act as the Single Point of Contact (SPOC) for Data Governance, Data Privacy, and Compliance.
- Own code quality and scalability across markets.
- Inform requirements for data science platform development and the deployment roadmap for AI readiness in collaboration with the CDP Product Group.
- Innovation & Scalability
- Identify new tools and technologies to support AI adoption and AI readiness.
- Measure and improve data science code and framework efficiency.
- Drive the continuous evolution of data science frameworks in collaboration with internal and external stakeholders.
- MLOps & Deployment
- Manage new model deployment pipelines.
- Maintain all existing consumer segmentation products.
- Ensure the reliability and performance of the data science framework.
- Coordinate data science releases across markets.
- Data Science Enhancements Program Leadership
- Own backlog prioritization for data science feature enhancements based on business value, market readiness, data availability and quality, and compliance constraints.
- Align prioritization with the Consumer Segmentation team and CDP Product Group.
- Ensure timely delivery of the backlog.
- Be responsible for bug fixing, code releases, and on-call support for the CDP Product Group.
- Contractor & GBS Management
- Supervise contractor work.
- Ensure knowledge transfer between contractors, GBS, and FTE employees.
- Own data science documentation and code versioning.
- Background & Experience
- 7-10 years of experience in ML engineering and/or data engineering.
- Strong experience with MLOps and cloud environments.
- Strong experience with AI/ML deployment environments.
- Experience managing technical teams and/or contractors.
- Understanding of databases and data modelling, including Oracle, Microsoft SQL Server, My SQL, and programming languages such as Python or R.
- Exposure to data science and statistical methodologies.
- Key Competencies & Skills
- Strong technical expertise.
- System architecture thinking.
- Delivery focus.
- Stakeholder collaboration.
- Problem-solving mindset.
- Our commitment to inclusion
PMI is on a continuous journey to ensure that all of our employees feel welcome and feel that they belong.
We have a number of internal networks that are inclusive and open for anyone to join, including networks covering employees from ethnic minority backgrounds, LGBTQ+ and gender.
We’re also extremely proud to be the first global company to be awarded Equal Salary Certification.
We take wellbeing seriously, so we have trained mental health First Aiders to help support our employees, as well as support in the form of our Life Works app and Employee Assistance Programme.
PMI is an equal opportunities employer, hiring solely on merit and business need.
We encourage applications regardless of sex, gender identity, ethnicity, age, sexual orientation, gender reassignment, religion or belief, marital status, pregnancy, parenthood and disability.
If you require reasonable adjustments in any recruitment process with us, please make us aware.
Manager AI Innovation & Deployment for Segmentation in London employer: Philip Morris
At PMI, we are committed to fostering a dynamic and inclusive work environment where innovation thrives. As an AI Solution Architect, you will not only have the opportunity to shape cutting-edge AI architectures but also benefit from our strong focus on employee growth, with structured career management and development opportunities. Join us in the UK, Poland, or Portugal, and be part of a transformative journey towards a smoke-free future, while enjoying a competitive salary and a culture that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Manager AI Innovation & Deployment for Segmentation in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Philip Morris!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Philip Morris.
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We think you need these skills to ace Manager AI Innovation & Deployment for Segmentation in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Philip Morris, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Philip Morris. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Philip Morris
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Philip Morris!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
