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- Tasks: Join our team to develop AI models and analyse data for customer insights.
- Company: Nissan is a leading automotive manufacturer with a strong European presence and innovative technology.
- Benefits: Enjoy competitive salary, flexible working hours, remote options, and comprehensive health benefits.
- Why this job: Be part of a dynamic team shaping the future of customer experience in the automotive industry.
- Qualifications: Degree in Data Science or related field; experience in machine learning and data analysis required.
- Other info: Diversity and inclusion are core values; all applicants are welcome.
The predicted salary is between 30000 - 45000 £ per year.
Join to apply for the Global Data Scientist role at Nissan Motor Corporation.
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.
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.
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.
What We Offer
- Competitive base salary
- 26 days holiday + bank holidays
- Contributory pension
- Private medical & dental cover
- Enhanced maternity leave
- Remote Working Policy
- Flexible start / finish times
- Free onsite parking
- Car Ownership Scheme
What's more, we think you'll like working with us because of our valued culture. We pride ourselves on being a transparent, cross-cultural and competitive business; we want you to challenge the norm and contribute to improvement whether you've been here ten days or ten years, so apply now to join CEC!
We firmly believe that investment in our employees is integral to their growth and success. As a member of our team, you will have access to many of our benefits - because we want you to feel cared for, supported, and engaged at Nissan. Alongside comprehensive career development and learning opportunities, you will also have access to a wide range of employee benefits. This includes an attractive car ownership scheme, flexible working practices, comprehensive health & wellbeing offerings and team building days.
Diversity and Inclusion: All of us at Nissan - regardless of functional area or expertise - share a passion to design, manufacture and sell high-performance, fun to drive vehicles. Nissan is an Equal Opportunity Employer for all. Applicants will be considered for all positions regardless of race, gender, military status, disability, or any other status protected by law.
Please note, it is a mandatory requirement to include your CV with your application. A cover letter may be submitted at your discretion.
Global Data Scientist employer: Nissan Motor Corporation
Contact Detail:
Nissan Motor Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Global Data Scientist
✨Tip Number 1
Familiarise yourself with Nissan's digital platforms and customer experience initiatives. Understanding how PACE operates and the role of the NCX team will help you demonstrate your enthusiasm and knowledge during interviews.
✨Tip Number 2
Showcase your hands-on experience with machine learning models by preparing examples of past projects. Be ready to discuss how you've applied advanced algorithms in real-world scenarios, especially in predictive analytics and customer segmentation.
✨Tip Number 3
Network with current or former employees of Nissan, particularly those in data science roles. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.
✨Tip Number 4
Prepare to discuss your approach to data analysis and insights generation. Be ready to explain how you would tackle large datasets and what tools you would use for exploratory data analysis, as this is crucial for the role.
We think you need these skills to ace Global Data Scientist
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Global Data Scientist position at Nissan. Tailor your application to highlight how your skills and experiences align with their needs.
Craft a Strong CV: Your CV should clearly showcase your experience in data science, machine learning, and any relevant projects. Use specific examples that demonstrate your problem-solving skills and technical expertise, particularly in AI and machine learning.
Write a Compelling Cover Letter: Although a cover letter is optional, it’s a great opportunity to express your enthusiasm for the role and the company. Discuss why you want to work at Nissan and how you can contribute to their goals, especially in enhancing customer experience through data.
Highlight Relevant Skills: Make sure to emphasise your proficiency in machine learning algorithms, data analysis, and any experience with cloud platforms or NLP tools. Mention any specific projects or achievements that demonstrate your capabilities in these areas.
How to prepare for a job interview at Nissan Motor Corporation
✨Showcase Your Technical Skills
As a Global Data Scientist, you'll need to demonstrate your expertise in machine learning and data analysis. Be prepared to discuss specific algorithms you've used, such as Decision Trees or Clustering techniques, and provide examples of how you've applied them in real-world scenarios.
✨Understand Nissan's Vision
Familiarise yourself with Nissan's goals, especially regarding customer experience and digital transformation. Showing that you understand their mission and how your role contributes to it will set you apart from other candidates.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Practice explaining your thought process when tackling complex data challenges, and be ready to discuss how you would approach developing AI solutions that align with business needs.
✨Communicate Clearly
Since you'll be working with non-technical stakeholders, it's crucial to convey technical concepts in an understandable way. Practice explaining your past projects and findings in simple terms, ensuring that anyone can grasp the significance of your work.
