Home › Companies › Fabledata › Data Scientist
Data Scientist
Fabledata · London, SE1 0HS, United Kingdom · Hybrid · Active · BambooHR
Job facts
| Field | Value |
|---|---|
| Company | Fabledata |
| Title | Data Scientist |
| Normalized title | - |
| Department / team | Data & Technology |
| Location | London |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | BambooHR |
| Posted / first seen | 2026-04-07 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Fabledata. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through BambooHR. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in London. | Open |
| Department jobs | Active postings in Data & Technology. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Fabledata |
| Source | 03d577b7-8b16-476a-bec7-a01aaeef5be5 |
| ATS provider | BambooHR |
Description
Location: London, UK (London)
Work pattern: Full-Time (Hybrid: minimum two days per week in our London office), PAYE
Salary: £45,000 - 55,000k per annum, DOE, generous options
Level: Mid, 2-3 years of relevant experience
Reporting line: Senior Data Scientist
Division/Team: Data Science (D&T)
We regret we are currently unable to provide visa sponsorship; please only apply if you have the right to work in the UK.
Application Process: When submitting your application, please answer each question to be considered for this role.
About Fable Data:
Fable Data is a global consumer transaction data company. We aggregate anonymised consumer data from financial services businesses which we then enrich and productise to deliver high value data products to some of the world’s leading retailers, investment managers, technology companies, governments, and advertising firms. Our data provides a near real-time view of the consumer economy, offering powerful insights into consumer behaviour, retailer performance and broader macroeconomic trends.
About the Role:
We’re looking for a talented Data Scientist ready to take the next step in their career; someone who thrives on analysing text data and is adept at using AI alongside an expansive machine learning toolkit to build high precision solutions to identify real world entities within billions of lines of text data.
With access to one of the most comprehensive, market leading, multi-country consumer transaction datasets available, you will expand the merchant vocabulary (named entity recognition), build new models and enhance the accuracy of our existing models that power our world class products and the high impact insights produced by our client enablement and commercial teams.
About You:
Passionate about solving real-world problems through a blend of applied data science, analytical thinking and research.
Curious with an eye for accuracy, you’re passionate about uncovering patterns in text that haven’t yet been discovered and can do so without compromising intellectual integrity and accuracy.
Product-driven thinking enables you to systematise your work into reusable and repeatable processes that can be integrated easily into our data platform.
You thrive in a fast-paced, collaborative environment that values both analytical rigour and commercial impact.
What you’ll do:
Key responsibilities:
Support the training, monitoring and improvement of a suite of data science models (primarily text-based classification models)
Assist in the development of new product concepts
Support the review and evaluation of potential new datasets
Assist in developing and implementing efficient strategies for creating high-quality labelled training datasets, leveraging automation, weak supervision, and active learning techniques
Design, implement, and maintain rule-based data processing logic leveraging regex and other pattern-matching approaches
Assist in developing monitoring systems for in-life machine learning models that automatically detect and flag issues
Work with stakeholders to define and implement new machine learning applications based on transaction data
Skills / knowledge:
Essential
2+ years’ experience working with large datasets in a commercial or academic environment.
Experience in SQL and Python in a professional context.
Fast learner and comfortable with uncertainty and change; we are a scale-up
Comfortable working with data cleaning, transformation, and basic scripting tasks.
Strong attention to detail and a focus on data quality.
Desirable
Experience monitoring and enhancing in-life ML Models (MLOps).
Familiarity with regex or willingness to learn quickly.
Knowledge of or experience with developing production code and source control via Git.
Knowledge of or experience with Spark/Databricks.
Familiarity with classification, time series, and/or natural language processing.
Knowledge of or experience working with consumer data, banking data, or stocks and shares.
Planning skills to help you prioritise work across multiple projects.
Why Fable
At Fable, we believe in continuous improvement and shared responsibility . You’ll join a collaborative team that empowers you to take ownership of your work, experiment, and grow your skills. This is a unique opportunity to combine technical depth with commercial storytelling and have your work seen by some of the most influential organisations in the world.
Full job record
| Job ID | 7840811a5b54f9036b593f0341ad381b5fb91ff9 |
| Org ID | 8f9a16f8-3066-4d83-8e5b-3c26b4d66028 |
| Source ID | 03d577b7-8b16-476a-bec7-a01aaeef5be5 |
| Board ID | 03d577b7-8b16-476a-bec7-a01aaeef5be5 |
| Provider | bamboohr |
| Provider Job Key | 127 |
| Title | Data Scientist |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | London, SE1 0HS, United Kingdom |
| Department | Data & Technology |
| Team | — |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | — |
| Region | — |
| City | London |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://fabledata.bamboohr.com/careers/127 |
| Apply URL | https://fabledata.bamboohr.com/careers/127 |
| First Seen At | 2026-05-30 05:39:03Z |
| Last Seen At | 2026-06-06 19:33:45Z |
| Last Checked At | 2026-06-06 19:33:45Z |
| Last Changed At | 2026-05-30 05:39:03Z |
| Inactive At | — |
| Source Posted At | 2026-04-07 00:00:00Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=bamboohr/board=fabledata/date=2026-06-06/2026-06-06T19-33-44-076Z-5bfa17c07a95e279469421a2c5aa3dbb6c9fa5ff83e0a3f1fc0daaad33f160d6.json |
Event Fields
{
"content_hash": "0d94fd920be8d61dd847b0e6216132e0297f464c5a03706d77f6c2f1adb23af5",
"source_hash": "eb725784f602a324a5fc7b3b379791a2be61e97000cd2f401511078b27fa986d",
"last_changed_at": "2026-05-30T05:39:03.319Z",
"active_status": "active"
}Parsed Structured
{
"language": "en",
"location": {
"raw": "London, SE1 0HS, United Kingdom",
"city": "London",
"region": null,
"country": null,
"is_remote": false,
"confidence": 0.8
},
"salary_max": null,
"salary_min": null,
"inferred_at": "2026-06-06T19:33:45.074Z",
"launch_scope": {
"reason": "bamboohr_production_catalog",
"included": true,
"location": {
"raw": "London, SE1 0HS, United Kingdom",
"city": "London",
"region": null,
"country": null,
"is_remote": false,
"confidence": 0.8
},
"countries": []
},
"remote_policy": "hybrid",
"salary_period": null,
"workplace_type": "hybrid",
"salary_currency": null
}Extensions
{}Native Structured
{
"list_job": {
"id": "127",
"isRemote": null,
"location": {
"city": "London",
"state": null
},
"atsLocation": {
"city": null,
"state": null,
"country": null,
"province": null
},
"departmentId": "18803",
"locationType": "2",
"jobOpeningName": "Data Scientist",
"departmentLabel": "Data & Technology",
"employmentStatusLabel": "Full-Time"
},
"detail_errors": [],
"detail_job_opening": {
"location": {
"city": "London",
"state": null,
"postalCode": "SE1 0HS",
"addressCountry": "United Kingdom"
},
"datePosted": "2026-04-07",
"atsLocation": {
"city": null,
"state": null,
"country": null,
"countryId": null
},
"description": "<p><span style=\"font-weight: bold\">Location:</span> London, UK (London)</p>\n<p><span style=\"font-weight: bold\">Work pattern:</span> Full-Time (Hybrid: minimum two days per week in our London office), PAYE</p>\n<p><span style=\"font-weight: bold\">Salary:</span> £45,000 - 55,000k per annum, DOE, generous options</p>\n<p><span style=\"font-weight: bold\">Level:</span> Mid, 2-3 years of relevant experience</p>\n<p><span style=\"font-weight: bold\">Reporting line: </span> Senior Data Scientist<br><br></p>\n<p><span style=\"font-weight: bold\">Division/Team: Data Science (D&T)<br><br></span></p>\n<p><span style=\"font-weight: bold\"><em>We regret we are currently unable to provide visa sponsorship; please only apply if you have the right to work in the UK.</em></span></p>\n<p><br><br></p>\n<p><span style=\"font-weight: bold\">Application Process: </span>When submitting your application, please answer each question to be considered for this role.</p>\n<p> </p>\n<p><span style=\"font-weight: bold\">About Fable Data:</span></p>\n<p>Fable Data is a global consumer transaction data company. We aggregate anonymised consumer data from financial services businesses which we then enrich and productise to deliver high value data products to some of the world’s leading retailers, investment managers, technology companies, governments, and advertising firms. Our data provides a near real-time view of the consumer economy, offering powerful insights into consumer behaviour, retailer performance and broader macroeconomic trends.</p>\n<p> </p>\n<p><span style=\"font-weight: bold\">About the Role:</span></p>\n<p>We’re looking for a talented <span style=\"font-weight: bold\">Data Scientist </span>ready to take the next step in their career; someone who thrives on analysing text data and is adept at using AI alongside an expansive machine learning toolkit to build high precision solutions to identify real world entities within billions of lines of text data.</p>\n<p>With access to one of the most comprehensive, market leading, multi-country consumer transaction datasets available, you will expand the merchant vocabulary (named entity recognition), build new models and enhance the accuracy of our existing models that power our world class products and the high impact insights produced by our client enablement and commercial teams.</p>\n<p> </p>\n<p><span style=\"font-weight: bold\">About You:</span></p>\n<ul>\n<li>Passionate about solving real-world problems through a blend of applied data science, analytical thinking and research.</li>\n<li>Curious with an eye for accuracy, you’re passionate about uncovering patterns in text that haven’t yet been discovered and can do so without compromising intellectual integrity and accuracy.</li>\n<li>Product-driven thinking enables you to systematise your work into reusable and repeatable processes that can be integrated easily into our data platform.</li>\n</ul>\n<ul>\n<li>You thrive in a fast-paced, collaborative environment that values both analytical rigour and commercial impact.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">What you’ll do:</span> </p>\n<p><span style=\"font-weight: bold\">Key responsibilities:</span></p>\n<ul>\n<li>Support the training, monitoring and improvement of a suite of data science models (primarily text-based classification models)</li>\n<li>Assist in the development of new product concepts</li>\n<li>Support the review and evaluation of potential new datasets</li>\n<li>Assist in developing and implementing efficient strategies for creating high-quality labelled training datasets, leveraging automation, weak supervision, and active learning techniques</li>\n<li>Design, implement, and maintain rule-based data processing logic leveraging regex and other pattern-matching approaches</li>\n<li>Assist in developing monitoring systems for in-life machine learning models that automatically detect and flag issues</li>\n<li>Work with stakeholders to define and implement new machine learning applications based on transaction data</li>\n</ul>\n<p> </p>\n<p><span style=\"font-weight: bold\">Skills / knowledge:</span></p>\n<p><span style=\"font-weight: bold\">Essential </span></p>\n<ul>\n<li>2+ years’ experience working with large datasets in a commercial or academic environment.</li>\n<li>Experience in SQL and Python in a professional context.</li>\n<li>Fast learner and comfortable with uncertainty and change; we are a scale-up</li>\n<li>Comfortable working with data cleaning, transformation, and basic scripting tasks.</li>\n<li>Strong attention to detail and a focus on data quality.</li>\n</ul>\n<p><span style=\"font-weight: bold\"><em>Desirable</em></span></p>\n<ul>\n<li>Experience monitoring and enhancing in-life ML Models (MLOps).</li>\n<li>Familiarity with regex or willingness to learn quickly.</li>\n<li>Knowledge of or experience with developing production code and source control via Git.</li>\n<li>Knowledge of or experience with Spark/Databricks.</li>\n<li>Familiarity with classification, time series, and/or natural language processing.</li>\n<li>Knowledge of or experience working with consumer data, banking data, or stocks and shares.</li>\n<li>Planning skills to help you prioritise work across multiple projects.</li>\n</ul>\n<p><em> </em></p>\n<p><span style=\"font-weight: bold\">Why Fable</span></p>\n<p>At Fable, we believe in <span style=\"font-weight: bold\">continuous improvement</span> and <span style=\"font-weight: bold\">shared responsibility</span>. You’ll join a collaborative team that empowers you to take ownership of your work, experiment, and grow your skills. This is a unique opportunity to combine technical depth with commercial storytelling and have your work seen by some of the most influential organisations in the world.</p>",
"compensation": "£45,000 - £55,000 per annum",
"departmentId": "18803",
"locationType": "2",
"seekPromoted": false,
"jobCategoryId": null,
"jobOpeningName": "Data Scientist",
"departmentLabel": "Data & Technology",
"jobOpeningStatus": "Open",
"minimumExperience": "Mid-level",
"jobOpeningShareUrl": "https://fabledata.bamboohr.com/careers/127",
"employmentStatusLabel": "Full-Time"
}
}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/7840811a5b54f9036b593f0341ad381b5fb91ff9?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/8f9a16f8-3066-4d83-8e5b-3c26b4d66028JSONGET https://api.bluedoor.sh/job-postings/v1/sources/03d577b7-8b16-476a-bec7-a01aaeef5be5JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/7840811a5b54f9036b593f0341ad381b5fb91ff9/eventsJSON