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Fractional Data Analyst (6–8 Hours per Week) – FinTech / Remote
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Please Read The Full Job Description Before Applying
Location: Remote
Working Pattern: Fractional – approximately 6–8 hours per week
Environment: Early-Stage FinTech
About The Opportunity
Our client is an early-stage FinTech developing a data-driven technology proposition within financial services.
As the organisation develops its product and commercial capability, it is looking for a hands-on Fractional Data Analyst to help turn growing volumes of business and product data into meaningful analysis, insight and decision support.
This is an early-stage environment.
You will not be joining a large established Data function with perfectly structured datasets, mature reporting infrastructure and predefined analytical processes.
The successful candidate will therefore need to be comfortable working with ambiguity, identifying data-quality issues and helping establish analytical processes as the organisation develops.
Further details regarding the engagement and participation structure will be discussed directly with candidates progressing through the process.
Application – Mandatory Qualifying Questions
Please submit your CV together with a cover letter. Within your cover letter, you must answer each of the mandatory qualifying questions below.
- How many years of professional Data Analyst or equivalent analytical experience do you have, and in what environments?
- What is your level of SQL proficiency? Please provide an example of a complex analysis or data problem you have personally solved using SQL.
- What experience do you have cleaning, validating and analysing incomplete or inconsistent datasets?
- Which data-visualisation and business-intelligence tools have you used professionally? Please explain your level of hands-on experience with each.
- Please provide an example where analysis you personally conducted materially influenced a product, commercial, credit, risk or operational decision.
- What experience do you have using Python or other analytical/programming tools? Please describe how you have used them rather than simply listing the technology.
- Do you have experience analysing financial-services, FinTech, payments, lending, credit, business or other complex datasets? Please explain.
- What experience do you have working directly with non-technical stakeholders to understand a business question and translate it into useful analysis?
- This opportunity requires approximately 6–8 hours per week. Can you consistently commit to this level of involvement alongside your other professional commitments?
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These questions are mandatory and form part of our initial assessment process. Applications that do not provide a clear answer to every mandatory qualifying question will be automatically disqualified and will not be considered further in the recruitment process.
What You'll Be Doing
You will provide hands-on analytical support across the developing organisation, including:
- Analysing business, product and operational datasets
- Writing and maintaining SQL queries
- Cleaning and validating data
- Identifying data-quality issues
- Exploring patterns, trends and anomalies
- Developing dashboards and reports
- Translating business questions into analytical approaches
- Presenting findings clearly to non-technical stakeholders
- Supporting Product, Risk and commercial decision-making
- Helping establish appropriate metrics and KPIs
- Supporting data-driven experimentation and evaluation
- Documenting analytical methodologies where appropriate
- Helping improve the consistency and usability of data as the company develops
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What We're Looking For
You may be a strong fit if you have:
- Professional Data Analyst or equivalent experience
- Strong practical SQL capability
- Experience manipulating imperfect real-world datasets
- Strong analytical reasoning
- Experience with data visualisation / BI tools
- Some practical Python or comparable analytical-programming capability
- Strong attention to detail
- Ability to identify questionable data rather than blindly report it
- Ability to explain findings clearly to non-technical audiences
- Strong problem-solving skills
- Ability to work independently
- Comfort operating within an early-stage environment where not everything has already been defined
Experience within FinTech, financial services, credit, payments, lending, banking or other data-rich regulated environments would be particularly valuable.
We will consider candidates from adjacent industries where they can demonstrate sufficiently strong analytical capability.
Engagement Structure
This is a flexible, fractional engagement of approximately 6–8 hours per week within an early-stage FinTech venture.
It is designed for someone comfortable contributing specialist analytical capability alongside other compatible professional commitments and with a structure centred on longer-term participation in company growth rather than a conventional package at this stage.
Full details of the participation structure will be discussed with candidates progressing through the process.
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