Senior Data Scientist - Marketing Mix Modeling | Hybrid Intelligence
Madrid, M, ES
Capgemini
A global leader in consulting, technology services and digital transformation, we offer an array of integrated services combining technology with deep sector expertise.Who we are?
We are Capgemini Engineering, part of the Capgemini Group.
Leaders in engineering services and R&D, with more than 65,000 people dedicated to Engineering and Science around the world. We help our clients accelerate their journey to smart industry, bringing global expertise and capabilities, cutting-edge digital technologies and software, agile engineering platforms and an industrialized execution model.
About the role
Our Hybrid Intelligence team at Capgemini Engineering is responsible for intelligently applying data science and machine learning technologies to deliver innovative and multidisciplinary solutions to our clients. We work for different sectors such as: Aerospace, Automotive, Pharma, Engineering, Industrial, Oil & Gas, among others.
As part of this team you will work on a wide variety of innovative projects that make a difference, merging applied mathematics, scientific computing, Artificial Intelligence and software engineering.
Main Challenges
- Supervision of the Data Scientist team in the Marketing department.
- Communication with business in the different countries involved.
- Design, develop and evaluate data-driven algorithms.
- Develop and improve PoC algorithms to meet product requirements.
- Follow trends in AI and ML literature and implement state-of-the-art approaches.
- Contribute clean and readable code to a deployable code base Regularly interact with and provide feedback to stakeholders and software engineers.
- Generate and test working hypotheses in a self-directed manner.
You should have:
- Bachelor's, Master's or PhD degree (preferred) in Computer Science, Data Science, Statistics or related field.
- At least 5 years of experience as Data Scientist / Machine Learning Engineer.
- Extensive experience in Marketing Mix Modelling.
- Excellent Python programming skills.
- Experience in standard machine learning techniques (e.g. linear regression, K-nn, SVM, PCA, Kmeans, random forest, boosting).
- Knowledge of econometrics, marketing.
- Knowledge of mathematics: linear algebra, statistics, probability theory, discrete and continuous optimisation.
- Proficient in Git version control.
- Fluency in English and Spanish (C1) and strong communication skills.
What we offer:
- Permanent contract.
- Flexible and Hybrid working model.
- 24 days holiday + 2 additional days + December 24th and 31st.
- Life and Accident Insurance.
- Restaurant ticket or meal subsidy.
- Flexible Compensation Plan (medical insurance, childcare, transport, training).
- Continuous training, you will be able to enjoy Mylearning and Capgemini University with access to platforms such as: Coursera, Udemy, Pluralsight, Harvard Manager Mentor, among others.
- Language training in English, French and German with Education First (EF).
Why should you join Capgemini Engineering?
- World leader in engineering.
- Relevant projects in innovation and R&D
- Part of a responsible company committed to equal opportunities.
- Multi-sector and multi-disciplinary expertise.
- Technology communities with a focus on continuous learning and improvement.
- Diverse, young-spirited teams that create a unique working environment!
Diversity is key to our strategy
Our commitment to inclusion and equal opportunities means that we have an Equality Plan and a Code of Ethics that guarantee the professional development of our staff and equal opportunities in their selection within an environment free of discrimination based on ethnicity, nationality, social origin, age, sexual orientation, gender expression, religion or any other personal, physical, or social circumstance.
At Capgemini Engineering we value all applications, don't hesitate to apply! #LI-JTA
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Computer Science Econometrics Engineering Git Industrial Linear algebra Machine Learning Mathematics Pharma PhD Probability theory Python R R&D Statistics
Perks/benefits: Career development Flex hours Startup environment
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