At a Glance
- Tasks: Support the implementation of a machine learning AML platform and collaborate with diverse teams.
- Company: Join AMS, a global leader in workforce solutions, fostering inclusive workplaces.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Other info: Exciting role with potential for extension and dynamic career development.
- Why this job: Make a real impact in financial crime detection using cutting-edge machine learning technology.
- Qualifications: Experience in data analysis, machine learning, and strong SQL skills required.
The predicted salary is between 50000 - 65000 £ per year.
AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces.
We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent strategies.
Our Contingent Workforce Solutions (CWS) is one of our service offerings.
Acting as an extension of their recruitment teams, we connect them with skilled interim and temporary professionals, fostering workplaces where everyone can contribute and succeed.
Our client, a major UK retail bank, provides every day banking services to over 17 million retail customers.
The banks expertise and services span across Business Services, Corporate banking, Wealth Management, Group Functions, Retail and Investment Banking.
On behalf of this organisation, AMS are looking for a Business/Data Analyst with strong experience in machine learning system implementation, for a 6 month contract (with potential for extension) based in the London office (hybrid model, 2 days a week in the office).
Purpose of the role
The Business/Data Analyst will support the implementation of our client's transaction monitoring system from a Legacy rules-based environment to a Machine Learning-driven AML platform.
This role sits within the Product team and will play a key role in defining requirements, supporting model development and ensuring effective financial crime detection outcomes within a fast-paced agile programme.
What you'll do
- Gather and document business and AML requirements.
- Work with Product Owner and tech teams to define scope and data needs.
- Translate financial crime risks into system and data requirements.
- Support the implementation of a machine learning AML solution.
- Work with data teams to define and validate model inputs and outputs.
- Assist with model training, testing, and tuning (calibration).
- Extract and analyse data (SQL/Mongo DB) to support decision making.
- Validate that model outputs align with AML risk scenarios.
- Collaborate with AML, Compliance, Data, and Tech teams.
- Explain technical concepts in a clear way.
The skills you'll need
- Proven Business Analyst/Data Analyst experience on technology change, implementation projects ideally, in moving from rules based to machine learning.
- Strong SQL (or Mongo DB) skills, able to analyse data independently.
- Experience working with data (customer/transaction data).
- Experience working in Agile delivery environments.
- Ability to translate business needs into data/technical requirements.
- Experience with Machine Learning/AI projects.
- Python skills.
- Exposure to model training, testing, or tuning (desirable).
- Experience in Transaction Monitoring (highly desirable) or Financial Crime/AML (desirable).
- Next steps
This client will only accept workers operating via an Umbrella or PAYE engagement model.
If you are interested in applying for this position and meet the criteria outlined above, please click the link to apply and we will contact you with an update in due course.
AMS, a Recruitment Process Outsourcing Company, may in the delivery of some of its services be deemed to operate as an Employment Agency or an Employment Business
Business/Data Analyst (ML system implementation) employer: Alexander Mann Solutions
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StudySmarter Expert Advice🤫
We think this is how you could land Business/Data Analyst (ML system implementation)
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Alexander Mann Solutions before they're even advertised!
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Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Business/Data Analyst (ML system implementation)
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Alexander Mann Solutions, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Alexander Mann Solutions, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Alexander Mann Solutions’s attention and show the tangible impact of your work.
How to prepare for a job interview at Alexander Mann Solutions
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Alexander Mann Solutions.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Alexander Mann Solutions.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Alexander Mann Solutions.
