Contract Senior Analyst Data Pilots, Data Exploration and Partnerships

[What you will be working on]

Technical Design & Feasibility Assessment:

• Partner with Data Partnership Managers in later-stage discussions with potential data partners to finalise the scope and specifications of data exchange.

• Act as the technical expert, assessing the quality, structure, and feasibility of using STB’s and our partner's data.

• Help translate business problems into specific, testable analytical questions.

Hands-on Data Analysis & Prototyping:

• Take the lead on the entire technical pilot process: data ingestion, cleaning, and transformation of new and diverse datasets.

• Perform advanced exploratory data analysis (EDA) using Python to uncover hidden patterns, correlations, and insights that go beyond basic reporting.

• Apply statistical methods to test hypotheses with rigour and build simple predictive models where applicable.

• Lead technical discovery and experimentation, defining your own hypotheses and analytical approaches to uncover the most valuable insights.

• Design and build compelling, interactive proof-of-concept dashboards (using tools like AWS QuickSight) that answer business questions clearly to non-technical stakeholders.

Insight Generation & Storytelling:

• Synthesize complex analytical findings into clear, concise insights and recommendations.

• Collaborate with the Data Partnership Manager to present pilot findings back to internal and external stakeholders, demonstrating the value of the data collaboration.

• Where possible and relevant, stretch the data pilots to include predictive and prescriptive insight.

Knowledge Transfer & Scaling Preparation:

• Meticulously document the data sources, cleaning logic, analytical methodologies, and code for successful pilots.

• Create a "recipe book" for each successful pilot that enables a smooth handover to the Data & AI Product Manager for evaluation and potential productisation onto our core Data and Analytics platform, STAN.

[What we are looking for]

Technical and Analytics skills:

• Trained in a quantitative field such as Data Analytics, Computer Science, Statistics, Engineering, or Economics.

• At least 3 years of demonstrable, hands-on experience in exploratory data analysis, data ingestion, transformation (cleaning, aggregation), and data modeling using large, real-world datasets.

• Strong proficiency in statistical programming (e.g., Python) and database scripting (SQL) is essential.

• Proven ability to develop compelling data visualizations and dashboards. Experience with tools like AWS QuickSight is highly advantageous.

• Solid applied statistical knowledge (e.g., regression, classification, significance testing).

• A portfolio of projects (e.g., via GitHub, a personal website, or a slide deck) showcasing your hands-on data analysis and coding work is required.

Work Approach:

• Collaborative Partner: A strong team player who sees yourself as the technical counterpart to our business-facing managers. You are comfortable owning your technical workstream end-to-end while working closely with others to achieve a shared goal.

• Comfortable with Ambiguity: A self-starter who thrives in an environment where priorities evolve and the path isn't always clear. You can take a vague business problem and messy data, and proactively find a path forward without waiting for instructions.

• Accountable & Driven: Balance creativity and exploration with discipline and follow-through. You take ownership of your projects, manage your timelines effectively, and are responsible for communicating progress and challenges clearly.

• The Pragmatic Storyteller: Strong analytical skills with a good eye for detail, but you also know how to translate complex technical findings into clear, concise language that a business audience can understand and act upon.

• A Continuous Learner: Humble and curious, open to feedback, new techniques, and better ways of working in a dynamic, fast-paced environment.