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- Tasks: Develop and deploy ML models, design production-grade pipelines, and mentor junior team members.
- Company: Join a leading FMCG/Retail client in London, driving innovation in data science.
- Benefits: Enjoy a competitive day rate, hybrid work options, and the chance to influence best practices.
- Why this job: Be part of a dynamic team, work on impactful projects, and enhance your skills in a collaborative environment.
- Qualifications: 5+ years as a Data Scientist with expertise in ML, Python, and SQL required.
- Other info: This is a contract role for 6 months, starting ASAP.
My new client is looking for a Senior or Principal Data Scientist with strong experience in machine learning, statistical modelling, and production-level ML systems. Must have experience building and shipping production-level ML pipelines in some cloud platform and writing production level code, working closely with Engineers.
Key Responsibilities:
- Develop and deploy ML models and statistical analyses, including time series forecasting, clustering, and econometrics
- Design and implement production-grade ML pipelines using modern cloud platforms (AWS, Azure, or GCP)
- Write clean, maintainable Python code and performant SQL for data wrangling, analysis, and model deployment
- Collaborate with engineers and cross-functional stakeholders to scale models and insights into production environments
- Take technical ownership of projects, mentor junior team members, and influence data science best practices
Requirements:
- 5+ years of hands-on experience as a Data Scientist, with a strong portfolio of real-world projects
- Expertise in machine learning and statistical modelling techniques (time series, clustering, econometrics preferred)
- Strong proficiency in Python and SQL
- Comfortable working in engineering-focused teams and writing production-level code
Senior Data Scientist (MLOps, AWS, Python) – Retail – Hybrid employer: Salt Digital Recruitment
Contact Detail:
Salt Digital Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (MLOps, AWS, Python) – Retail – Hybrid
✨Tip Number 1
Make sure to showcase your experience with MLOps and cloud platforms like AWS in your conversations. Highlight specific projects where you've built and deployed ML models, as this will resonate well with the hiring team.
✨Tip Number 2
Prepare to discuss your approach to writing clean, maintainable Python code. Be ready to share examples of how you've collaborated with engineers to ensure that your ML pipelines are production-ready.
✨Tip Number 3
Familiarise yourself with the latest trends in machine learning and statistical modelling techniques, especially time series forecasting and clustering. This knowledge will help you stand out during discussions about your technical expertise.
✨Tip Number 4
Demonstrate your leadership skills by discussing any mentoring experiences you've had with junior team members. This will show that you're not only technically proficient but also capable of guiding others in best practices.
We think you need these skills to ace Senior Data Scientist (MLOps, AWS, Python) – Retail – Hybrid
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning, statistical modelling, and production-level ML systems. Include specific projects where you've built and deployed ML models, especially using AWS or Python.
Craft a Strong Cover Letter: In your cover letter, emphasise your hands-on experience as a Data Scientist and your ability to collaborate with engineers. Mention any mentoring roles you've had and how you've influenced data science best practices in previous positions.
Showcase Relevant Projects: Include a portfolio or a section in your CV that showcases real-world projects relevant to the job description. Highlight your expertise in time series forecasting, clustering, and econometrics, and provide details on the impact of your work.
Proofread and Format: Before submitting your application, proofread all documents for clarity and grammatical accuracy. Ensure your CV and cover letter are well-formatted and easy to read, making it simple for recruiters to find key information.
How to prepare for a job interview at Salt Digital Recruitment
✨Showcase Your Portfolio
Make sure to bring along a strong portfolio of your real-world projects. Highlight specific examples where you've developed and deployed ML models, especially in production environments. This will demonstrate your hands-on experience and technical expertise.
✨Demonstrate Technical Skills
Be prepared to discuss your proficiency in Python and SQL. You might be asked to solve coding problems or explain your approach to writing clean, maintainable code. Brush up on your coding skills and be ready to showcase your ability to write performant SQL queries.
✨Understand MLOps Principles
Since the role involves MLOps, ensure you understand the principles behind building and shipping production-level ML pipelines. Be ready to discuss your experience with cloud platforms like AWS, Azure, or GCP, and how you've implemented these in past projects.
✨Collaboration is Key
This position requires collaboration with engineers and cross-functional teams. Prepare examples of how you've worked in engineering-focused teams and influenced data science best practices. Highlight any mentoring experiences with junior team members as well.
