Senior Data Scientist / Data Engineer

Senior Data Scientist / Data Engineer, London [Onsite - 5 days/wk]

<£140,000 base + discretionary bonus [dependent on experience]

We are partnered with a specialist investment manager, with a long track record of performance, that is looking to hire a Senior Data Scientist / Data Engineer to join its growing tech function. The firm is going through a period of significant data transformation, and this hire is fundamental to driving that modernisation. The role will drive the scientific and analytical side of a lean, hands-on team that sits close to the business. Because the team is small, the remit is deliberately broad, spanning analysis, modelling, engineering and stakeholder engagement. It's a role providing substantial autonomy and visibility.

The successful candidate will help shape a new data platform in Snowflake that brings together investment, operational, market and reference data from front, middle and back office systems. The focus is on getting real value from that data and includes: exploratory analysis, building and validating analytical models, and helping the firm put AI and machine learning to practical use. This role will suit a highly entrepreneurial individual who thrives without a set playbook and wants a broad, hands-on role in a small team that is growing its data capability.

Responsibilities:

• Leading exploratory and statistical analysis on investment and operational data to surface trends, drivers and issues for senior stakeholders
• Owning the development and validation of analytical models, such as data quality scoring and anomaly detection, and taking them through to reliable, monitored use
• Building the pipelines, datasets and data models in Snowflake that the firm’s analysis and models rely on, with a focus on quality and reconciliation against source systems
• Applying AI and machine learning tooling across the data platform and development lifecycle, and setting the standard for how it’s adopted responsibly
• Delivering insight through dashboards in Sigma or a similar BI tool, and explaining methods, assumptions and limitations clearly to Investment, Operations, Risk and Technology colleagues

Requirements:

• 6+ years’ experience in data science or analytics with a strong engineering element, ideally in financial services
• Strong Python, including the data science stack (pandas, NumPy, scikit-learn or similar), and strong SQL
• A good grounding in statistics, with hands-on experience building and validating models
• Experience with a cloud data warehouse such as Snowflake, Databricks, BigQuery or Redshift, and with data modelling and ETL
• A strong degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics or Engineering, and a proactive approach suited to working autonomously

This opportunity is being advertised anonymously. If you would like to talk it through before sending a CV, submit a blank application and one of the team will be in touch.

Due to the high level of interest, we can only respond to applicants whose background closely matches the brief.