Data Scientist

7 days left

Columbia Threadneedle Investments
London, United Kingdom
26 Feb 2023
28 Mar 2023
Job Function
Industry Sector
Finance - General
Employment Type
Full Time
About Columbia Threadneedle Investments

You'll find the promise we make to our clients is the same one we make to our employees: Your success is our priority.

Here, you'll find growth and career opportunities across all our businesses. We're intentionally built to help you succeed. Our reach is expansive with a global team of 2,000 people working together. Our expertise is diverse with more than 450 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 welcome applications from returners to the industry.

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.

Job Purpose Statement

Where you'll fit in & what our team goals are....

As a Data Scientist, you will play an integral role in supporting modelling and data analysis for Columbia Threadneedle Investments. Own the creation and/or usage of large data sets, providing information-based decision logic and predictive modelling solutions, and translates modelling/analytic output into understandable/practical business knowledge, insight and applications. Demonstrate strong technical/problem solving skills. Support multiple projects collaboratively.

Role Responsibilities

How you'll spend your time....
  • Identify, develop and implement sophisticated analytical solutions leveraging tools such as predictive modelling, advanced machine learning techniques, simulation, optimisation solutions, etc..
  • Handle dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation. May supervise execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.
  • Under direction of the Sr. Leader, collaborate 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 modelling and analytic output into understandable and useful business knowledge.
  • Embed analytic programs and tools. Ensure continued accuracy, relevancy, and efficiency and track operational improvements once deployed.
  • Ensure adherence to data and model governance standards that are set and implemented by industry standards and/or enterprise and business unit data governance polices and leaders.
  • Supply 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 standardised/automated solutions and adopt best practices.

Key Capabilities

To be successful in this role you will have....
  • Established experience in a similar role or equivalent educational qualification in a Quantitative Subject area (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.)
  • Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
  • Experience conducting hands-on analytics projects using sophisticated statistical methods such as generalised regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies.
  • Experience with statistical programming (Python,R,SQL etc.) & data visualisation software in a data-rich environment.
  • Experience in AWS services such as Redshift, S3, Sagemaker will be an advantage
  • Proven track record to present/communicate complex, technical materials in a way that facilitates decision making and drives outcomes; ability to communicate to less technical partners.
  • Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.
  • Ability to work effectively in a collaborative team environment