Description review
Fractional Data Analyst (6–8 Hours per Week) – FinTech / Remote
Rosie's People · United Kingdom · back to the listing
HR standards
70/100
solid
Title ↔ description
88/100
strong
Reads as
Data Analyst
100% confident
What this role officially is
data analyst — ESCO, the EU occupation classification
Data analysts import, inspect, clean, transform, validate, model, or interpret collections of data with regard to the business goals of the company. They ensure that the data sources and repositories provide consistent and reliable data. Data analysts use different algorithms and IT tools as demanded by the situation and the current data. They might prepare reports in the form of visualisations such as graphs, charts, and dashboards.
Also known as: data warehousing analyst, data analysts, data warehouse analyst, data storage analyst
How others title the same work
Large employers
- Operations Insights, Tax Stripe
Startups
- Senior Data Analyst Camber
- Senior Data Analyst Confido
What the listing never says
- 34 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Fractional Data Analyst (6–8 Hours per Week) – FinTech / Remote
PLEASE READ THE FULL JOB DESCRIPTION BEFORE APPLYING1
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?
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
PLEASE READ THE FULL JOB DESCRIPTION BEFORE APPLYING1
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?
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