WHO ARE WE?

Nissan has one of the most comprehensive European presences of any overseas manufacturer, employing more than 17,000 staff across locally based Design, Research & Development, Manufacturing, Logistics, Purchasing and Sales & Marketing operations. Total production in the UK alone is now over 9 million vehicles including award-winning crossovers, commercial vehicles and the Nissan LEAF, the world’s most popular electric vehicle.
We are an aspiring organisation, and we are looking for equally bold and creative Global Data Scientist to join our established team. Nissan is positioned to become the most desirable Asian brand in Europe, and we need your help to get there.

SKILLS & EXPERIENCE REQUIRED

• Proven experience in Data Science, Advanced Analytics, and Statistical Modeling.
• Expertise in supervised and unsupervised machine-learning algorithms, including Decision Trees, Random Forest, CatBoost, Clustering techniques (K-means, DBSCAN, etc.), and Time Series Forecasting.
• Knowledge of cloud platforms (GCP, AWS, or Azure) and version control tools such as Git.
• Strong problem-solving and communication skills, capable of explaining technical concepts to non-technical audiences.
• Experience in developing Large Language Models is a plus.
• Degree in Data Science, Computer Science, or a related field.
• Experience in productionizing machine learning models and working with APIs for data extraction.
• Experience with NLP including Text Classification, Sentiment Analysis, and Topic Modelling using tools like NLTK, BERT, and GCP NLP API.
• Fluent in English, both verbal and written

PURPOSE

The digital experience is at the heart of the relationship between brands and their customers. The Nissan Global Customer Experience (NCX) team aims to offer customers with the best experience through market leading technology for their online and offline interactions with the different Nissan brands, be it through a computer, a mobile phone or a tablet, or personal experience with Nissan representatives. This is enabled through PACE (Platform for Accelerated Customer Experience) which powers all of Nissan’s 150 websites across the globe, which this team is responsible for developing, optimising and rolling out new experiences across Nissan.

MAIN TASKS & RESPONSIBILITIES

In this role you will be joining CEDAR (Customer Experience Data, Analytics & Reporting) team within NCX to drive the value that can be derived from the data generated by millions of interactions each day across 145 markets from visitors to our digital channels and connected cars. For this we are looking for a hands-on Data Scientist with advanced machine learning skills combined with practical business acumen.

AI & Machine Learning Model Development

• Develop, test, and deploy AI and machine learning models for integration into data platforms.
• Ensure models meet business requirements for predictive analytics, customer segmentation, and process optimization.
• Engineer features from raw data to enhance model accuracy and performance.
• Apply statistical techniques to analyse data and uncover patterns.
• Implement validation and monitoring strategies to maintain model accuracy over time.

Data Analysis & Insights

• Analyse large and complex datasets to extract actionable insights that drive business value.
• Work closely with data engineers and analysts to prepare and transform data for model development.
• Generate insights from data using Exploratory Data Analysis (EDA) and model interpretability tools such as SHAP and LIME.
• Undertake preprocessing of structured and unstructured data, including text processing and cleaning for NLP applications.

Strategic Collaboration & Product Development

• Work with product managers and stakeholders to ensure AI solutions align with business needs and customer expectations.
• Contribute to the development of data products by integrating AI capabilities that enhance functionality and user experience.
• Brief product domains and channel owners on strategic initiatives and goals.
• Monitor the performance of journey initiatives and provide recommendations based on insights.

Compliance & Documentation

• Document methodologies, processes, and model specifications to ensure transparency and reproducibility.
• Ensure AI models and processes adhere to data security and privacy regulations.
• Collaborate with data governance teams to maintain compliance and implement ethical AI practices.