Machine Learning Operations Engineer – 11328SR7 in Bristol
Machine Learning Operations Engineer – 11328SR7

Machine Learning Operations Engineer – 11328SR7 in Bristol

Bristol Full-Time 34000 - 51000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Develop and optimise machine learning models to predict financial outcomes.
  • Company: Leading financial services firm 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 financial sector.
  • Qualifications: Experience in machine learning, Python, and data management is essential.
  • Other info: Great career growth opportunities in a supportive 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 in Bristol employer: Proactive.IT Appointments Limited

Join a forward-thinking financial services firm in London that values innovation and collaboration. As a Machine Learning Operations Engineer, you'll benefit from a competitive salary, a discretionary bonus scheme, and a flexible benefits package designed to support your well-being and work-life balance. With opportunities for professional growth and a culture that encourages continuous learning, this hybrid role offers the perfect environment for you to thrive in the dynamic field of machine learning.
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Contact Detail:

Proactive.IT Appointments Limited Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Operations Engineer – 11328SR7 in Bristol

Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 and data management. 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 that extra step to engage with us directly.

We think you need these skills to ace Machine Learning Operations Engineer – 11328SR7 in Bristol

Machine Learning
Statistical Modelling
Azure ML
Data Management
Data Preprocessing
Python
SQL
CI/CD
DevOps
MLOps
Data Visualization
PowerBI
Communication Skills
Interpersonal Skills
Team Collaboration

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. Don’t forget to mention your experience in the financial services sector if you have it!

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 hit the ground running!

Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. It’s super easy, and you’ll be able to keep track of your application status directly!

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 prepared to explain how you developed them, the algorithms you chose, and the outcomes they predicted. This shows your technical expertise and ability to communicate complex concepts.

Showcase Your Azure ML Skills

Since this role involves using Azure ML, brush up on your experience with it. Be ready to talk about how you've designed, deployed, and maintained models in production environments. Highlight any specific challenges you faced and how you overcame them.

Demonstrate Data Management Know-How

Discuss your experience with data wrangling and preprocessing. Bring examples of how you've collected, cleaned, and managed large datasets. This will show that you understand the importance of data quality in model training and analysis.

Communicate Effectively with Non-Technical Stakeholders

Prepare to explain technical concepts in a way that's easy for non-technical team members to understand. Think of examples where you've successfully communicated complex ideas and how that helped your team or project. This skill is crucial for collaboration in a multidisciplinary environment.

Machine Learning Operations Engineer – 11328SR7 in Bristol
Proactive.IT Appointments Limited
Location: Bristol

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