Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead data analysis and predictive modelling to drive business insights.
- Company: Join a global investment firm committed to diversity and inclusion.
- Benefits: Flexible working options, career growth, and a supportive team environment.
- Why this job: Make an impact with advanced analytics in a collaborative setting.
- Qualifications: Experience in statistical programming and machine learning techniques.
- Other info: Opportunity to work with cutting-edge technologies and develop your skills.
The predicted salary is between 28800 - 48000 £ per year.
Where you’ll fit in & what our team goals are… You will play an integral leadership role in supporting modeling and data analysis and database needs for assigned line of business (Asset Management). You will manage or direct the creation and usage of large data sets, providing information-based decision logic and predictive modeling solutions, and translate modeling/analytic output into understandable/actionable business knowledge, insight and applications. You will also provide analytic thought leadership and support in a lead business relationship role whilst demonstrating strong technical/problem solving skills.
How you’ll spend your time…
- Identify, develop and implement increasingly complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, etc.
- Engage collaboratively with business leaders and/or analysts to provide analytical thought leadership and support for business problems.
- Identify and interpret business needs, define high-level business requirements, strategy, technical risks, and scope.
- Develop, document, and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.
- Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation.
- May monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.
- Contribute to ongoing expansion of data science expertise and credentials by keeping up with industry best practices, developing new skills, and knowledge sharing.
- Work cross functionally to develop standardized/automated solutions and adopt best practices.
- May provide technical advice and coaching to business analysts on best practices for usage and application of analytic output.
- Embed analytic programs and tools.
- Ensure continued accuracy, relevancy, and effectiveness and track process improvements once deployed.
- Ensure adherence to data and model governance standards that are set and enforced by industry standards and/or enterprise business unit data governance policies and leaders.
- May lead or provide informal leadership to a team of analytic resources.
To be successful in this role you will have…
- Knowledge of advanced statistical concepts and techniques, e.g. skilled in linear algebra.
- Experience conducting hands‑on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies.
- Experience with statistical programming (Python, SQL are must-haves while other programming languages like SAS and R are preferred) & data visualization software in a data‑rich environment.
- Demonstrated project experience while working with AWS/Azure/Snowflake.
- Proven executive presence communication skills, with the ability to translate complex digital performance data into clear, actionable insights that influence prioritization and investment; ability to communicate to less technical partners.
- Strong experience partnering with senior leaders to drive aligned, data‑informed decisions and business outcomes.
- Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.
- Ability to work effectively in a collaborative team environment.
If you also had this, it would be great…
- Experience with big data technologies, Cloud Computing Environments (including container creation, management & deployment), Spark, etc.
- MBA or advanced degree in analytics, economics, statistics, or related field.
- Experience working in regulated industries or highly matrixed, enterprise environments.
- Experience modernizing or scaling enterprise experimentation programs and attribution frameworks.
- Track record of leading analytics organizations through significant transformation or maturity shifts.
About Columbia Threadneedle Investments Working at Columbia Threadneedle Investments you’ll find growth and career opportunities across all of our businesses. We’re intentionally built to help you succeed. Our reach is expansive with a global team of 2,500 people working together. Our expertise is diverse with more than 650 investment professionals sharing global perspectives across all major asset classes and markets. Our clients have access to a broad array of investment strategies, and we have the capability to create bespoke solutions matched to clients' specific requirements. Columbia Threadneedle is a people business and we recognise that our success is due to our talented people, who bring diversity of thought, complementary skills and capabilities. We are committed to providing an inclusive workplace that supports the diversity of our employees and reflects our broader communities and client‑base. We appreciate that work‑life balance is an important factor for many when considering their next move so please discuss any flexible working requirements directly with your recruiter.
Data Scientist employer: Threadneedle group
Contact Detail:
Threadneedle group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues 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 data science projects, especially those using Python, SQL, or machine learning techniques. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and 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 by the right people. Plus, it shows you're genuinely interested in joining our team at Columbia Threadneedle Investments.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with advanced statistical methods and data analysis. We want to see how your skills align with the specific needs of the Data Scientist role.
Showcase Your Technical Skills: Don’t hold back on showcasing your programming skills, especially in Python and SQL. We’re looking for candidates who can demonstrate hands-on experience with these tools, so include relevant projects or examples in your application.
Communicate Clearly: Remember, we value the ability to translate complex data into actionable insights. Use clear and concise language in your application to show us you can communicate effectively with both technical and non-technical stakeholders.
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 shows you’re keen on joining our team!
How to prepare for a job interview at Threadneedle group
✨Know Your Data Science Tools
Make sure you’re well-versed in the tools mentioned in the job description, like Python and SQL. Brush up on your knowledge of advanced statistical methods and be ready to discuss how you've applied them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your technical and problem-solving abilities. Think of specific instances where you identified a business need and developed an analytical solution that had a real impact.
✨Communicate Clearly
Practice translating complex data insights into simple, actionable recommendations. You’ll need to demonstrate that you can communicate effectively with both technical and non-technical stakeholders.
✨Engage Collaboratively
Be ready to discuss how you’ve worked cross-functionally in the past. Highlight your experience in collaborating with business leaders and analysts to drive data-informed decisions and outcomes.