At a Glance
- Tasks: Develop and optimise machine learning models to predict outcomes in financial services.
- Company: Leading financial services firm based in London with a hybrid work culture.
- Benefits: Competitive salary, bonus scheme, flexible benefits, and 25 days holiday.
- Why this job: Join a dynamic team and make a real impact in the world of finance with cutting-edge technology.
- Qualifications: Experience in machine learning, Python, and Azure ML; strong communication skills are essential.
- Other info: Great career growth opportunities in a supportive and innovative environment.
The predicted salary is between 34000 - 51000 £ per year.
Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role, working from home and their offices in London.
To be considered for the role you must have the following essential skills & experience:
- Model development: Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision‑making processes, and improve client offerings.
- Machine Learning Operations: Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large‑scale data efficiently. Implement and maintain monitoring of model drifts, data‑quality alerts, scheduled re-training pipelines.
- Data Management and Preprocessing: Collect, clean and preprocess large datasets to facilitate analysis and model training. Implement data pipelines and ETL processes to ensure data availability and quality.
- Software Development: Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review. Work closely with actuarial analysts, actuarial modelling team (AMT) and other colleagues in the company to integrate data science findings into practical advice and strategies. Stay abreast of new trends and technologies in Data Science technologies and pensions to identify opportunities for innovation. Provide training and support to other team members on using machine learning tools and understanding analytical techniques. Interpret and explain machine learning concepts and findings to other members of the analytics team and non‑technical stakeholders within the company.
Technical Skills required:
- Previous experience in designing, building, optimising, deploying and managing business‑critical machine learning models using Azure ML in Production environments.
- Experience in data wrangling using Python, SQL and ADF.
- Experience in CI/CD and DevOps/MLOps and version control.
- Familiarity with data visualization and reporting tools, ideally PowerBI.
- Good written and verbal communication and interpersonal skills.
- Ability to convey technical concepts to non‑technical stakeholders.
- Experience in the pensions or similar regulated financial services industry is highly desirable.
- Experience in working within a multidisciplinary team would be beneficial.
Benefits:
- We offer an attractive reward package; typical benefits can include:
- Competitive salary
- Participation in Discretionary Bonus Scheme
- A set of core benefits including Pension Plan, Life Assurance cover and employee assistance programme, 25 days holiday and access to a qualified, practising GP 24 hours a day/365 days a year
- Flexible Benefits Scheme to support you in and out of work, helping you look after you and your family covering Security & Protection, Health & Wellbeing, Lifestyle
Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted. Proactive Appointments Limited operates as an employment agency and employment business and is an equal opportunities organisation. We take our obligations to protect your personal data very seriously. Any information provided to us will be processed as detailed in our Privacy Notice, a copy of which can be found on our website.
Machine Learning Operations Engineer – 11328SR7 employer: Proactive.IT Appointments Limited
Contact Detail:
Proactive.IT Appointments Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Operations Engineer – 11328SR7
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. 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 machine learning projects, especially those using Azure ML. 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 common technical questions related to machine learning operations. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage with us directly.
We think you need these skills to ace Machine Learning Operations Engineer – 11328SR7
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Operations Engineer role. Highlight your experience with Azure ML, Python, and any relevant projects that showcase your skills in model development and data management.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with the job description. Don’t forget to mention your experience in the financial services sector if applicable!
Showcase Your Technical Skills: Be specific about your technical skills in your application. Mention your familiarity with CI/CD practices, data wrangling, and any tools like PowerBI that you’ve used. This will help us see how you can contribute to our team right away.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Proactive.IT Appointments Limited
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've worked on in detail. Be ready to explain how you developed them, the algorithms you chose, and the outcomes they predicted. This shows your depth of knowledge and ability to apply theory to practice.
✨Showcase Your Azure ML Skills
Since this role involves using Azure ML, be prepared to talk about your experience with it. Discuss specific projects where you designed, deployed, or optimised models. Highlight any challenges you faced and how you overcame them to demonstrate your problem-solving skills.
✨Communicate Clearly with Non-Technical Stakeholders
Practice explaining complex machine learning concepts in simple terms. You might be asked to convey technical findings to non-technical team members, so being able to break down jargon will set you apart. Use examples from past experiences to illustrate your points.
✨Prepare for Data Management Questions
Expect questions about data preprocessing and management. Be ready to discuss your experience with data pipelines, ETL processes, and how you ensure data quality. This is crucial for the role, so having concrete examples will help you shine.