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- Tasks: Lead a team of data scientists to innovate and enhance supply chain efficiencies.
- Company: Join a forward-thinking company committed to diversity and innovation.
- Benefits: Enjoy hybrid remote work, competitive salary, and professional growth opportunities.
- Why this job: Make a real impact by applying advanced data science techniques in exciting projects.
- Qualifications: 7+ years in data science with strong skills in Python and machine learning.
- Other info: Collaborative environment with a focus on mentorship and career development.
The predicted salary is between 36000 - 60000 £ per year.
As the Data Science Team Lead, you will be developing tools and technologies that leverage data from a variety of sources to increase supply chain efficiencies and provide value to our customer.
Key Responsibilities May Include:
- Lead a team of data scientists, providing mentorship and guidance on daily tasks, fostering professional development and capability growth.
- Oversee the implementation of Continuous Integration/Continuous Deployment (CI/CD) pipelines, ensuring deliverables meet project milestones and quality standards.
- Apply advanced machine learning, forecasting, and statistical analysis techniques to drive experimentation and innovation on data science projects.
- Lead the experimentation and implementation of new data science techniques for projects, ensuring alignment with internal and external customer objectives.
- Communicate project status, methodologies, and results to both technical teams and business stakeholders, translating complex data insights into actionable strategies.
- Facilitate data science team discussions, providing technical expertise on current methods and guiding decision-making for optimal outcomes.
- Contribute to strategic data science initiatives, influencing the direction of key projects and aligning team efforts with broader business goals.
- Encourage collaboration across teams and functions to ensure seamless integration of data science solutions into business processes and technology platforms.
Experience:
- Experience in people and/or project management activities.
- Utilized multiple data science methodologies.
- Presented to non-technical audiences.
- Researched and implemented new data science techniques.
- Have worked autonomously and delivered results on schedule.
Qualifications:
- Essential: Degree in Data Science, Computer Science, Engineering, Science, Information Systems and/or equivalent formal training plus work experience.
- BS & 7+ years of work experience.
- MS & 6+ years of work experience.
- Proficient with machine learning and statistics.
- Proficient with Python, deep learning frameworks, Computer Vision, Spark.
- Have produced production level algorithms.
- Proficient in researching, developing, synthesizing new algorithms and techniques.
- Excellent communication skills.
- Desirable: Master’s or PhD level degree.
- 7+ years of work experience in a data science role.
- Proficient with cloud computing environments, Kubernetes, etc.
- Familiarity with Data Science software & platforms (e.g. Databricks).
- Software development experience.
- Research and new algorithm development experience.
Skills and knowledge:
- Demonstrable experience of machine learning techniques and algorithms.
- Experience with statistical techniques and CRISP-DM lifecycle.
- Commercial experience or experimental Jupyter notebooks to production.
- Production ML Experience: Deployed models that serve real users, ability of scale to million users without incurring technical debt.
- Strong programming skills in Python and familiarity with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.
- MLOPS experience with tools such as Drift, Decay, A/B Testing.
- Integration and Differential testing, python package building, code version etc.
- Experience with data pipeline creation and working with structured and unstructured data.
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) preferred.
- Excellent problem-solving skills combined with the ability to communicate complex technical concepts to non-technical stakeholders.
- Ability to mentor a team of Data Scientists, Machine Learning Engineers and Data Engineers with strategy making capability.
Remote Type: Hybrid Remote
We are an Equal Opportunity Employer, and we are committed to developing a diverse workforce in which everyone is treated fairly, with respect, and has the opportunity to contribute to business success while realizing his or her potential. This means harnessing the unique skills and experience that each individual brings and we do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state, or local protected class.
Data Science Principal in London employer: Brambles
Contact Detail:
Brambles Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Principal in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the hunt for a new role. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data science projects, especially those involving machine learning and statistical analysis. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex data insights in simple terms, as you'll need to translate technical jargon for non-technical stakeholders. We want you to shine!
✨Tip Number 4
Don't forget to apply through our website! It's the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Science Principal in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Science Principal role. Highlight your leadership experience, technical expertise, and any successful projects you've led. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how your background aligns with our goals. Don't forget to mention specific techniques or tools you've used that relate to the job description.
Showcase Your Communication Skills: Since you'll be translating complex data insights for non-technical stakeholders, it's crucial to demonstrate your communication skills in your application. Use clear, concise language and avoid jargon where possible. We love candidates who can make data accessible!
Apply Through Our Website: We encourage you to apply directly through our website. This ensures your application gets to the right people quickly. Plus, it shows us you're serious about joining our team at StudySmarter!
How to prepare for a job interview at Brambles
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning techniques and statistical methods. Be ready to discuss specific algorithms you've implemented and how they’ve impacted projects. This role is all about leveraging data, so show them you know your stuff!
✨Show Off Your Leadership Skills
As a Data Science Team Lead, you'll need to demonstrate your ability to mentor and guide others. Prepare examples of how you've led teams in the past, tackled challenges, and fostered professional growth. They’ll want to see your leadership style in action.
✨Communicate Like a Pro
You’ll be translating complex data insights for non-technical stakeholders, so practice explaining your work in simple terms. Think of ways to showcase your communication skills during the interview, perhaps by discussing a project where you had to present findings to a diverse audience.
✨Be Ready for Technical Questions
Expect some deep dives into your technical expertise, especially around Python, CI/CD pipelines, and cloud computing. Brush up on your knowledge of tools like TensorFlow and Kubernetes, and be prepared to discuss how you’ve used them in real-world scenarios.
