At a Glance
- Tasks: Lead and deliver machine learning solutions, mentoring teams and deploying models on AWS.
- Company: Dynamic tech firm focused on innovative data science projects.
- Benefits: Competitive pay, hybrid work model, and opportunities for professional growth.
- Other info: Join a fast-paced team with excellent career advancement potential.
- Why this job: Make a real impact by shaping the future of machine learning in a collaborative environment.
- Qualifications: Strong Python skills, ML experience, and AWS deployment knowledge required.
The predicted salary is between 60000 - 80000 £ per year.
- Principal Data Scientist / ML Consultant (Contract)
- Duration: 6 Months
- Engagement: Full-Time Contract
- Working Model: Hybrid (UK-based)
- Overview
- We are seeking a hands-on
Principal Data Scientist / ML Consultant to lead the delivery of an existing machine learning programme through to a production-grade AWS deployment .
This role requires someone who can provide technical leadership, mentor internal teams, and actively build, deploy, and operationalise machine learning solutions.
Key Responsibilities
- Design and develop predictive models to support commercial decision-making.
- Utilise Auto ML tools (e. g. Auto Gluon, H2O Auto ML, Py Caret) to accelerate model development.
- Assess, prepare, and engineer data for modelling.
- Deploy and operationalise ML solutions within AWS.
- Implement MLOps practices including monitoring, retraining, and model governance.
- Provide technical leadership and knowledge transfer to internal teams.
- Manage stakeholder communication, providing clear recommendations and updates.
Essential Skills
- Strong hands-on Python and machine learning experience.
- Proven track record delivering ML solutions into production.
- Experience with Auto ML frameworks.
- Strong understanding of regression, forecasting, and predictive analytics.
- Data engineering and pipeline development capability.
- AWS ML deployment experience (e. g. Sage Maker, ECS, Lambda).
- Practical MLOps experience.
- Excellent stakeholder management and consulting skills.
- Experience mentoring data science teams.
- AWS-native ML tooling and cloud architecture experience.
- Experience delivering data-driven commercial or optimisation solutions.
- Deliverables
- Production-grade ML solution deployed in AWS.
- Established deployment, monitoring, and retraining processes.
- Knowledge transfer and upskilling of the internal team.
Principal Data Scientist / Principal ML Consultant in England employer: ECS Resource Group
ECS Resource Group is an exceptional employer, offering a dynamic work environment in Oxford where clinical excellence and professional development are at the forefront. With a strong emphasis on collaboration and evidence-based practices, employees benefit from comprehensive training opportunities and a supportive culture that fosters growth within the healthcare sector. Join us to make a meaningful impact in surgical solutions while enjoying the unique advantages of working in a vibrant city known for its rich history and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Data Scientist / Principal ML Consultant in England
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We think you need these skills to ace Principal Data Scientist / Principal ML Consultant in England
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at ECS Resource Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ECS Resource Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at ECS Resource Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ECS Resource Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
