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- Tasks: Design and build advanced machine learning models for customer data science.
- Company: Join a global leader in Customer Data Science, working with top businesses and retailers.
- Benefits: Enjoy a hybrid work model and competitive salary up to £60,000.
- Why this job: Be at the forefront of ML/AI advancements while collaborating with a dynamic team.
- Qualifications: PhD in relevant fields and strong coding skills in Python, R, or MATLAB required.
- Other info: Stay updated with the latest tech trends and enhance existing ML models.
The predicted salary is between 42000 - 60000 £ per year.
This company is a global leader in Customer Data Science, working across customer analytics and loyalty as a consultancy service, giving you the opportunity to work with market-leading businesses and retailers!
They are looking for a Data Scientist to join their Data Science team!
RESPONSIBILITIES:- Work on designing and building advanced ML models - including propensity and clustering
- Apply machine learning, statistical, and econometric methods to a range of other customer data science problems
- Work closely within a team to understand, troubleshoot, and maintain machine learning models
- Maintain and enhance existing ML models, ensuring all models deployed in production are monitored
- Stay updated with the latest developments in ML/AI and related fields to keep the company at the forefront of technological advancements
- PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields
- Proven experience in clustering and propensity
- Strong coding skills in Python, R or MATLAB
- Excellent communication skills
- Knowledge of databases and SQL
Register your interest by sending your CV to Joseph Gregory via the Apply link on this page.
KEYWORDS:Data Science, Machine Learning, Retailers, Pricing, Price optimisation, Demand Forecasting, Customer, cluster, propensity
Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and data science. Follow relevant blogs, attend webinars, and participate in online forums to stay updated. This knowledge will not only help you in interviews but also show your genuine interest in the field.
✨Tip Number 2
Network with professionals in the data science community. Join LinkedIn groups or local meetups focused on data science and machine learning. Engaging with others in the industry can lead to valuable connections and insights about job opportunities.
✨Tip Number 3
Prepare to discuss your previous projects in detail, especially those involving clustering and propensity models. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your practical experience and problem-solving skills.
✨Tip Number 4
Showcase your coding skills by contributing to open-source projects or creating your own GitHub repository. Highlighting your ability to write clean, efficient code in Python, R, or MATLAB will set you apart from other candidates and prove your technical capabilities.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data science, particularly focusing on your skills in machine learning, clustering, and propensity modelling. Use specific examples from your past work to demonstrate your expertise.
Craft a Strong Cover Letter: Write a cover letter that not only expresses your enthusiasm for the role but also outlines how your PhD and experience align with the company's needs. Mention your coding skills in Python, R, or MATLAB and your familiarity with databases and SQL.
Showcase Your Projects: If you have worked on any relevant projects, especially those involving machine learning models, be sure to include them in your application. Describe your role, the technologies used, and the outcomes achieved to give a clear picture of your capabilities.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data science roles.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, R, or MATLAB in detail. Bring examples of projects where you've applied machine learning techniques, especially clustering and propensity models, to demonstrate your expertise.
✨Communicate Clearly
Since excellent communication skills are a requirement, practice explaining complex data science concepts in simple terms. This will help you connect with interviewers who may not have a technical background.
✨Stay Updated on Industry Trends
Research the latest developments in machine learning and AI. Being able to discuss recent advancements or trends during your interview will show your passion for the field and your commitment to staying at the forefront of technology.
✨Prepare for Team Collaboration Questions
As the role involves working closely within a team, think of examples from your past experiences that highlight your ability to collaborate effectively. Be ready to discuss how you troubleshoot and maintain machine learning models as part of a team.
