Fractional Data Analyst (6–8 Hours per Week) – FinTech / Remote

Fractional Data Analyst (6–8 Hours per Week) – FinTech / Remote

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.

1. How many years of professional Data Analyst or equivalent analytical experience do you have, and in what environments?
2. What is your level of SQL proficiency? Please provide an example of a complex analysis or data problem you have personally solved using SQL.
3. What experience do you have cleaning, validating and analysing incomplete or inconsistent datasets?
4. Which data-visualisation and business-intelligence tools have you used professionally? Please explain your level of hands-on experience with each.
5. Please provide an example where analysis you personally conducted materially influenced a product, commercial, credit, risk or operational decision.
6. 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.
7. Do you have experience analysing financial-services, FinTech, payments, lending, credit, business or other complex datasets? Please explain.
8. What experience do you have working directly with non-technical stakeholders to understand a business question and translate it into useful analysis?
9. This opportunity requires approximately 6–8 hours per week. Can you consistently commit to this level of involvement alongside your other professional commitments?

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

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.

Originally posted on Himalayas