Details

Contract

Full-Time

Location

Lausanne, Switzerland

Department

Consumer

Openings

3

Job ID

55846028

Be a part of a revolutionary change. Times are changing at PMI. We’ve chosen to do something big. The world expects us to act responsibly. And we are doing just that by transforming our business and building our future on one clear purpose – to deliver a smoke-free future. This transformation will revolutionize every area of our business. The products we sell. Where we sell them. How they’re manufactured and delivered. The way we talk to our customers and engage with society. It’s the perfect setting place to start your career. As you take your first steps, you’ll have the backing of a multinational business combined with the freedom of a start-up. You’ll bring a positive mindset and fresh perspective to projects that can make a huge difference to so many. Are you up for a 6-month challenge starting in August 2023? Then apply now, we are waiting for you! About the TEAM You will join and work in close collaboration with Global Insights & Analytics team working on the biggest category in Philip Morris International in Lausanne acting as the cohesive force that underpins our consumer-centric and data-driven decision making. This internship provides an excellent opportunity to apply theoretical knowledge in a practical setting and contribute to data-driven decision-making processes on a global scale and learn from a mix of talents in data, analytics, science, technology, marketing and media. Who we’re looking for • Currently pursuing a degree in data science or a related field • Critical thinker who is able to define approaches to solving a business problem, understand the data and validate the findings. Ability to turn insights into powerful visualizations using tools (Power BI, etc) • Proficient in Python a for data manipulation, analysis, and modelling • Data extraction, data manipulation, and analysis; demonstrated strength using SQL queries in a business environment/ VBA • Solid understanding of machine learning algorithms and techniques • Knowledge of data pre-processing, feature engineering, and model evaluation • Ability to distill large data sets into meaningful insights and takeaways, ability to translate data insights into impactful presentations - familiarity with data visualization tools such as Power-BI or Tableau or PowerPoint • Excellent verbal and written communication skills in English, any other language is a plus • Ability to work effectively in a team-oriented and collaborative environment Roles & Objectives • Collaborate with cross-functional teams to understand business requirements and goals for the product recommender and performance forecasting system • Collect, pre-process, and analyse various relevant data using Python and SQL • Apply machine learning algorithms and techniques to develop a robust and accurate product recommender & performance forecasting system • Optimize and fine-tune the recommender system based on performance metrics • Plan A/B testing to evaluate the effectiveness of the recommender system • Develop data visualization dashboards and reports to communicate insights and recommendations to stakeholders • Stay up to date with the latest advancements in recommender systems and implement best practices • Document the development process, methodologies, and findings for future reference What we offer Our success depends on our talented employees who come to work here every single day with a sense of purpose and an appetite for progress. Join PMI and you too can: • Seize the freedom to shape your future and ours. We’ll empower you to take risks, experiment and explore. • Be part of an inclusive, diverse culture, where everyone’s contribution is respected; collaborate with some of the world’s best people and feel like you belong. • Pursue your ambitions and develop your skills with a global business –our staggering size and scale provides endless opportunities to progress. • Take pride in delivering our promise to society: to deliver a smoke-free future. PMI is an Equal Opportunity Employer.

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