Data, Analytics & Reporting Analyst - Data Engineering Team

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 2,300 people working together. Our capability is diverse with more than 550 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.

Our unwavering focus on our clients and strong financial foundation connects each of our enterprise businesses — Ameriprise Financial, Columbia Threadneedle Investments and River Source Insurance and Annuities.

Job Description Join our Data Engineering team and help shape the data, analytics and reporting capabilities that support investment oversight, research, portfolio construction and manager selection. You will partner with Coverage Analysts, Investment Strategy & Research and Multi-Manager Solutions professionals to translate complex business needs into high-quality data solutions, quantitative models and actionable reporting. This hands‑on role offers meaningful ownership, cross‑functional influence and the opportunity to strengthen data quality, automate critical workflows and introduce innovative analytical capabilities.

You will contribute directly to how our investment teams generate insights and make informed decisions while continuing to grow your technical and investment expertise.

Responsibilities Partner closely with Coverage Analysts, Investment Strategy & Research and Multi-Manager Solutions professionals to understand analytical needs and translate them into effective data solutions, models and reporting. Participate in research discussions and project planning, aligning data and analytical capabilities with investment oversight, research, portfolio construction and manager selection priorities. Source, validate and maintain investment data across platforms and databases, ensuring quality, consistency, accessibility and reliable data feeds for investment teams and broader stakeholders.

Build, maintain and enhance quantitative models, analytical tools and performance attribution systems, including solutions that support backtesting, scenario analysis and factor‑based research. Automate recurring analytical and reporting workflows to improve efficiency, accuracy and timely delivery of performance reports, risk metrics and strategy dashboards. Design and maintain dashboards and data visualisations that give investment professionals ready access to decision‑useful information. Apply sound model governance practices, including clear documentation, version control and validation protocols.

Drive process improvement by evaluating new technologies and methodologies, including artificial intelligence and machine learning, and support product development and market research through data analysis and quantitative modelling. Collaborate with Enterprise Technology, Information Technology and Investment Risk Management teams on technology enhancements, platform development and analytical needs, while coordinating effectively with colleagues across Boston, New York, London and India.

Required Qualifications Prior experience in data analytics, quantitative development or reporting within investment management or financial services, with strong knowledge of investment data, portfolio analytics, performance attribution and risk. Bachelor's or Master's degree in mathematics, statistics, computer science, data science or a related quantitative field. Advanced proficiency in Python, R and Structured Query Language (SQL), together with experience using database platforms.

Strong communication skills, with the ability to explain complex concepts clearly to technical and non‑technical audiences and collaborate across functions and locations. Proven ability to manage multiple priorities, deliver high‑quality work to deadlines and demonstrate initiative, intellectual curiosity and a practical problem‑solving mindset.

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