At a Glance
- Tasks: Transform machine learning models into robust pipelines and live APIs for real-world applications.
- Company: Join Hometrack, a leader in redefining the mortgage journey with innovative data services.
- Benefits: Enjoy flexible working, generous leave, wellness perks, and a supportive work environment.
- Other info: Dynamic team culture with excellent career growth and exciting projects.
- Why this job: Make a real impact by integrating cutting-edge machine learning solutions into essential products.
- Qualifications: Strong Python skills and experience with machine learning tools and cloud services required.
The predicted salary is between 60000 - 80000 £ per year.
Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.
We are looking for an experienced Senior Machine Learning Engineer to translate POC model code from data science and analytics into robust pipelines and live APIs.
Responsibilities:- Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time.
- Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services.
- Develop automated workflows for model retraining, testing, and deployment to streamline the machine learning lifecycle.
- Advocate for and implement best practices in software engineering, including code reviews, continuous integration, and continuous delivery (CI/CD) for machine learning models.
- Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control, testing frameworks, MLOps.
- Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code.
- Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM.
- Have worked with a cloud service, such as AWS.
- Familiarity developing Infrastructure as code (e.g Terraform, cloudformation).
- Have some experience with data engineering, building data pipelines with PySpark, SQL (E.g in Databricks, Glue) to power machine learning applications.
- Comfortable working with Docker and containerised applications.
- Experience leveraging AI native engineering tooling.
- Passion for building products that meet customer needs and business objectives.
- Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.
- Everyday Flex - greater flexibility over where and when you work
- 25 days annual leave + extra days for years of service
- Day off for your birthday, house move, good deed day, and digital detox day
- Cycle to work and electric car schemes
- Free Calm App membership
- Enhanced Paternity Leave
- Fertility Treatment Financial Support
- Group Income Protection and private medical insurance
- Gym on-site in London – or membership in regional offices
- 7.5% pension contribution by the company
- Discretionary annual bonus up to 10% of base salary
- Talent referral bonus up to £5K
Senior Machine Learning Engineer employer: Hometrack
Hometrack is an exceptional employer that champions innovation and collaboration in the financial services sector. With a strong focus on employee well-being, we offer flexible working arrangements, generous leave policies, and comprehensive benefits, including enhanced paternity leave and financial support for fertility treatments. Our vibrant work culture fosters professional growth through continuous learning opportunities, making it an ideal environment for Senior Machine Learning Engineers to thrive and contribute to meaningful projects.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Hometrack!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Machine Learning Engineer at Hometrack.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Hometrack.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Machine Learning Engineer at Hometrack, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Machine Learning Engineer
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 Hometrack, 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 Hometrack. 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 Hometrack
✨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 Hometrack!
✨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.
