Attercop on cord

Attercop

Data Scientist

External position
Brighton, UK
Hiring internally for Attercop?
Machine Learning and AI · Consultancy
Responsible AI for business impact
Posted
4 days ago
Checked
cord regularly checks that external positions are still open
2 days ago

Skills & Experience

Job roles: Data Scientist
Experience level: Senior
Core skills considered: Machine Learning, Python, Data Analysis
Other skills considered: Data Modeling, Data Pipelines, Deep Learning

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid
Visa sponsorship: Not available

Job Description

We are seeking an experienced Data Scientist to join Attercop's Applied Science and Engineering team to design, build, and evaluate AI and machine learning solutions across the full project lifecycle. The majority of our client problems involve unstructured text (extracting structure from documents, retrieving the right information from large and messy corpora, and applying generative models reliably enough to put in front of a client's users), so we are looking for genuine depth in natural language processing and machine learning. You will own model and system design, experimentation, and evaluation, while productionisation and infrastructure sit with our AI Engineers, with whom you'll work closely.


Responsibilities

  • Problem Framing: Translate ambiguous client requirements into well-posed machine learning problems with defined success criteria and realistic scope.
  • Modelling: Select, implement, and tune models appropriate to the problem and the data available, resisting unnecessary complexity where a simpler approach performs.
  • Statistical Rigour: Apply sound experimental design, validation strategy, and error analysis, including investigation of bias, data leakage, and distribution shift.
  • Data Exploration and Feature Engineering: Conduct thorough exploration of structured and unstructured data, and perform the cleaning, transformation, and feature construction needed to make it modellable.
  • Model Development: Design, fine-tune, and evaluate NLP models for tasks including classification, information extraction, entity recognition, summarisation, and semantic similarity.
  • Information Retrieval: Build and evaluate retrieval systems spanning sparse, dense, and hybrid approaches, including embedding model selection, chunking strategy, reranking, and query understanding.
  • Generative AI: Apply large language models to client problems through prompting, structured output, RAG architectures, and fine-tuning where warranted, with a clear understanding of each failure mode.
  • Evaluation Design: Define task-appropriate metrics and build evaluation harnesses for systems where ground truth is expensive, ambiguous, or subjective.
  • Ontology and Schema Design: Contribute to the taxonomies, ontologies, and graph schemas used to structure client domain knowledge.
  • Graph Construction from Text: Apply entity recognition, entity linking, and relation extraction to build knowledge graphs from unstructured sources.
  • Graph-Augmented Retrieval and Reasoning: Explore graph-based approaches to retrieval and reasoning where relational structure adds value beyond vector search alone.
  • Production-Ready Code: Write clean, well-tested, maintainable Python in line with Attercop's coding standards, contributing to shared codebases and reusable components.
  • Hand-Off and Integration: Work closely with AI Engineers to move models and pipelines into client systems, providing the documentation, tests, and interfaces required for a clean handover.
  • Tooling: Assist in evaluating and adopting new tools, frameworks, and techniques that enhance the team's capabilities and the quality of client deliverables.
  • Ownership: Take responsibility for the quality of your own output, seek peer review proactively, and escalate technical risks or blockers promptly and constructively.
  • Horizon Scanning: Stay current with developments in NLP, information retrieval, and generative AI, bringing relevant ideas and techniques to the attention of the wider team.
  • Prototyping: Contribute to internal R&D efforts, prototyping new approaches and helping to assess their viability for client applications.
  • Documentation: Record research findings, methodologies, and implementation details clearly, sharing knowledge with colleagues and, where appropriate, external audiences.

Requirements

  • We'd expect either:
    • A minimum of 3 years of professional experience as a Data Scientist or Research Scientist with a substantial proportion of that time spent on NLP or language-centric problems in a commercial or applied research setting, alongside a degree (or equivalent demonstrable experience) in a quantitative discipline such as computer science, mathematics, statistics, physics, or engineering; or
    • A PhD in one of those disciplines with a research focus on NLP or machine learning.
  • Machine Learning (essential):
    • Solid grounding in machine learning fundamentals, model evaluation, and experimental design.
    • Demonstrable experience building and validating models on real, imperfect data.
    • Working knowledge of scikit-learn and PyTorch, and comfort reading and adapting research code.
  • Natural Language Processing (essential):
    • Strong, demonstrable background in NLP, including hands-on work with transformer architectures, embeddings, and modern pre-trained models.
    • Proficiency with the current NLP toolchain, such as Hugging Face Transformers, spaCy, and sentence-transformers.
    • Practical experience with information retrieval and/or RAG systems, including how to measure and improve retrieval quality.
    • Demonstrated experience applying LLMs to real problems, with a clear-eyed view of where they work, where they fail, and how to tell the difference.
  • Python and Software Engineering (essential):
    • Strong proficiency in Python, including the core data stack (pandas, NumPy) and an understanding of how to structure code beyond a notebook.
    • Good software engineering practices, including version control (Git), automated testing, and code review.
    • Experience working with structured and unstructured data at scale, including cleaning, transformation, and pipeline construction.
  • Knowledge Graphs and Semantic Technologies (desirable):
    • Experience with knowledge graph construction or processing, ideally derived from text.
    • Familiarity with graph databases and query languages (e.g. Neo4j / Cypher, RDF / SPARQL) and with ontology or taxonomy design.
    • Awareness of graph-augmented retrieval approaches such as GraphRAG.
  • Cloud, Data, and MLOps (desirable):
    • Familiarity with cloud platforms (Azure preferred, or AWS/GCP) and with MLOps tooling for model deployment, versioning, and monitoring.
    • Experience with vector databases and semantic search infrastructure.
    • Experience with data engineering concepts, including pipelines, orchestration, and warehousing.
  • Wider Experience (desirable):
    • Experience working in a consultancy or client-facing environment.
    • Contributions to open-source projects, published research, or public writing on NLP or data science topics.
    • Familiarity with agentic frameworks such as LangChain and LangGraph.
  • Strategic and Collaborative Competencies:
    • Cross-Functional Collaboration: Work effectively within cross-functional project teams, supporting the Lead Data Scientist in planning, scoping, and delivering technical workstreams alongside AI Engineers, consultants, and client stakeholders.
    • Technical Communication: Articulate complex technical concepts, model limitations, and performance metrics clearly to both technical peers and non-technical leadership, through presentations, written reports, and informal discussion.
    • Client Engagement: Represent Attercop professionally in client meetings and workshops
Data Scientist at Attercop
Position posted 4 days ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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