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- Tasks: Develop machine learning models and optimisation techniques for decision-support software.
- Company: Leading tech firm at Heathrow, fostering innovation and collaboration.
- Benefits: Competitive daily rate, flexible working, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact in the tech industry.
- Qualifications: Master’s degree or 2+ years of relevant experience in data science or ML.
- Other info: Exciting projects with potential for career advancement in a fast-paced environment.
The predicted salary is between 54000 - 90000 £ per year.
Location: Heathrow, Waterside, UK
Job Type: Contract – Inside IR35
Rate: 450 GBP Per Day – Inside IR35
Role purpose: This role is responsible for developing industrialized optimisation and machine learning models as part of a full-stack product squad that delivers operations decision-support software.
Skills/capabilities:
- Strong knowledge of either machine learning and optimization techniques, including supervised (regression, tree methods, etc.), unsupervised (clustering) learning, and operations research (linear, mixed integer programming, heuristics).
- Fluent in Python (required) and other programming languages (preferred) with strong skills in applying data science, machine learning, and operations research packages (scikit-learn, pandas, numpy, gurobi, etc.) to solve real-life problems and visualise the outcomes (e.g. seaborn).
- Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g. MLflow).
- Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) - nice to have.
- Experience in code testing (unit, integration, end-to-end tests).
- Strong data engineering skills in SQL and Python.
- Proficient in use of Microsoft Office, including advanced Excel and PowerPoint skills.
- Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights.
- Understanding of the trade-offs of different data science, machine learning, and optimization approaches, and ability to intelligently select which are the best candidates to solve a particular business problem.
- Able to structure business and technical problems, identify trade-offs, and propose solutions.
- Communication of advanced technical concepts to audiences with varying levels of technical skills.
- Managing priorities and timelines to deliver features in a timely manner that meet business requirements.
- Collaborative team-working, giving and receiving feedback, and always seeking to improve team processes.
Qualifications/experience:
- Master’s degree or greater in data science, machine learning, or operational research, or 2+ years of highly relevant industry experience (required).
- 0-2 years working on production machine learning or optimization software products at scale (required).
- Experience in developing industrialized software, especially data science or machine learning software products (preferred).
- Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred).
Data Marketing Scientist in City of London employer: Avensys Consulting UK
Contact Detail:
Avensys Consulting UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Marketing Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that Data Marketing Scientist gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning models and optimisation techniques. We love seeing real-life applications of your work, so make sure to highlight those projects when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. We recommend practising common data science problems and being ready to discuss your thought process. Remember, they want to see how you tackle challenges, so don’t hold back!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are eager to join our team and make an impact in the data science world.
We think you need these skills to ace Data Marketing Scientist in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Marketing Scientist role. Highlight your experience with machine learning, optimisation techniques, and any relevant programming skills. We want to see how your background aligns with what we're looking for!
Showcase Your Projects: Include specific projects where you've applied data science or machine learning techniques. We love seeing real-life applications of your skills, so don’t hold back on the details about the tools you used and the outcomes you achieved.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your skills can contribute to our team. We appreciate a personal touch, so let your personality come through!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Avensys Consulting UK
✨Know Your Tech Inside Out
Make sure you’re well-versed in the machine learning and optimisation techniques mentioned in the job description. Brush up on your Python skills and be ready to discuss how you've applied libraries like scikit-learn and pandas in real-life scenarios.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data science problems in the past. Be ready to explain your thought process, the trade-offs you considered, and how you arrived at your solutions. This will demonstrate your analytical skills and ability to structure business problems.
✨Familiarise Yourself with Cloud Tools
Since experience with cloud platforms like AWS is preferred, make sure you understand the basics of tools like SageMaker and Docker. If you’ve used any cloud-based ML tools or CI/CD practices, be prepared to share your experiences and how they contributed to your projects.
✨Communicate Clearly and Confidently
You’ll need to explain advanced technical concepts to a variety of audiences, so practice articulating your ideas clearly. Use simple language when necessary and be ready to adapt your explanations based on who you’re speaking to. Good communication can set you apart!
