Data Analyst

The Dot Collective

ABOUT THE DOT COLLECTIVE We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact.  We work with all modern tech stacks and typically run agile scrum on all our projects. ABOUT YOU Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities:  * Gathering and documenting business and project requirements  * Managing stakeholders of differing levels  * Analysing and profiling large and complex datasets  * Managing a team backlog using tools like Jira or Azure DevOps  * Agile ways of working  * Familiar with Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) systems  * Creating conceptual, logical and physical data models   * Creating mapping specifications for data migrations  * Coordinating User Acceptance Testing (UAT) with business stakeholders  * Excellent SQL skills  * Knowledge of python (pandas)  * Experience with Cloud platforms  * Creating data dashboards using Tableau, PowerBI or Qlik and story telling  We expect you to work closely with business to understand their current data problems, pain points and to know how to analyse and cleanse their data. Also, we expect you to design data storage solutions and be a good communicator with your technical team.  OUR PROMISE TO YOU We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbaticals and ability to work on personal projects. We believe that a geled team is worth its weight in gold – we will do everything we can to avoid breaking well-performing teams. Whilst continuity across every project is not always possible, we thoughtfully assemble high-performing, blended teams with the appropriate levels of experience and expertise to deliver the best outcomes for our clients — and teams you’ll enjoy working with. We are committed to prioritising the wellbeing of our employees. To fulfill this promise, we provide a comprehensive employee wellbeing program that includes mental health support, flexible working arrangements, wellness activities, and a positive work culture. We recognise that the world of tech delivery has moved on significantly in the last 15 years and know a thing or two about how to bring projects over the line without experiencing lots of despair and burn-out. In fact, we like to believe that our projects are the opposite of that – they are run smoothly and most of the time are fun to work on.

Winton

ABOUT WINTON Winton is a research-based investment management company with a specialist focus on statistical and mathematical inference in financial markets. The firm researches and trades quantitative investment strategies, which are implemented systematically via thousands of securities, spanning the world's major liquid asset classes. Founded in 1997 by David Harding, Winton today manages assets for some of the world’s largest institutional investors. We employ ambitious professionals who want to work collaboratively at the leading edge of investment management. ----------------------------------------------------------------------------------------------------------------------------------   Winton leverages quantitative analysis and cutting-edge technology to identify and capitalize on opportunities across global financial markets. We foster a collaborative and intellectually stimulating environment, bringing together individuals with Mathematics, Physics and Computer Science backgrounds who are passionate about applying rigorous scientific methods to financial challenges. As a fundamentally data-driven business, our success is heavily linked to the acquisition, processing, and analysis of vast datasets. High-quality, well-managed data forms the critical foundation for our quantitative research, strategy development, and automated trading systems. As a Data Analyst within our Quantitative Platform team, you will own the quality, consistency, and discoverability of datasets as they move from onboarding into production. You will uphold our data standards and catalogue, so datasets are easy to find, trust, and use. Your work spans vendor-sourced financial data, time series across instruments and asset classes, and complex, multi-table products where correct mapping and definitions matter as much as raw data accuracy. Your responsibilities will include: * Defining and executing rigorous acceptance criteria for new and evolving data products. From sample evaluation through to production, including coverage analysis, staleness and gap detection, and reconciliation against trusted references where available. * Acting as a subject-matter expert on our data products, helping Strategy Managers with vendor formats, data anomalies, corporate actions semantics, identifiers, and documentation gaps; escalate and track issues with vendors and internal stakeholders until resolved.  * Building and maintaining an automated catalogue of datasets (descriptions, owners, refresh cadence, SLAs, source systems, schemas, known limitations). Keeping the catalogue aligned with reality when pipelines change so consumers rely on current metadata. * Systematically probe new and existing datasets to ensure they meet our high data quality standards. Stress-test point-in-time, versioning and revision semantics; chase down corrections, duplicates, staleness, and discontinuities with source vendors. * Contributing to data quality frameworks, onboarding checklists, and documentation (data dictionaries, lineage notes, known limitations) so quality expectations are repeatable and auditable. * Partnering with Data Engineers on handoff contracts (schemas, SLA expectations, alerting thresholds), with Quant Researchers on analytic sanity checks, and with operations on repeatable triage when anomalies appear in production datasets. What we are looking for: * 3+ years’ experience working with financial data vendors and their products. * Strong grasp of cross-asset class time series data and what common or nuanced issues can arise when onboarding new datasets. * Comfort with complex, multi-entity datasets (join keys, slow-changing dimensions, snapshots vs history) and a methodical approach to debugging inconsistencies. * Hands-on analytical experience using Python, and the ability to summarize findings clearly for both technical and non-technical audiences. * Meticulous attention to detail and a bias toward evidence-based conclusions. * Excellent communication and collaboration skills, and the ability to work in a team in a fast-moving, data-centric environment. What would be advantageous: * Direct experience with reference and hierarchical data (security masters, classification trees, entity relationships) and cross-vendor alignment. * Familiarity with market, fundamental, or alternative datasets used in systematic or quantitative investment workflows. * Exposure to data quality tooling or statistical monitoring (distributions, drift, anomaly detection) applied to production or near-production feeds.  * Experience building ETL/ELT pipelines using Python. * Practical experience using LLMs to accelerate complex data investigations.   ---------------------------------------------------------------------------------------------------------------------------------- EQUAL OPPORTUNITY WORKPLACE We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.

Liberis

Please note that Liberis is unable to provide visa sponsorship for this position. Therefore, all candidates must have full rights to work in the UK for a minimum of 2 years.   At Liberis, our mission is to empower small and medium-sized businesses by removing finance as a friction to growth, delivering contextual, embedded financial solutions to support merchants at every stage of their business lifecycle.     The team We are the Risk team responsible for managing the credit risk of Liberis’ portfolios, which include designing effective new strategies, managing the credit quality of our products across geographies, and providing specialist credit risk advice to the business. The Risk team is based in London and covers Risk analytics, Decision Science, Underwriting and Collections. Our mission is to grow Liberis profitably to become the leading embedded business finance provider and we are now looking for a Credit Risk Analyst to join us on this journey.   The role   We're looking for someone who enjoys solving complex problems through data and analysis. This is an ideal role for an analytical thinker who is naturally curious, enjoys investigating trends and identifying opportunities, and is motivated by seeing their work influence real business decisions. You'll be comfortable taking ownership of projects - framing problems, conducting deep analysis, developing recommendations and working with stakeholders to implement change. While experience in credit risk is beneficial, we're primarily looking for an individual with strong analytical capability, commercial thinking and a track record of turning data into actionable insights. Reporting to the Risk Manager, you'll help shape Liberis' credit risk strategy by delivering analytical insights, developing portfolio monitoring frameworks and driving strategic initiatives across our global products. You'll work closely with teams across Risk, Data Science, Analytics, Product, Pricing and Commercial to ensure our lending decisions support sustainable growth while remaining within our risk appetite.     What you will be doing   * Own analytical projects from initial problem definition through to recommendation and implementation. * Perform deep-dive analyses to identify portfolio trends, emerging risks and opportunities for improvement. * Develop and optimise credit risk strategies across the customer lifecycle, including acquisition and collections. * Build and enhance forecasting models to provide forward-looking insight into portfolio performance and emerging trends. * Design and maintain portfolio monitoring frameworks and dashboards, transforming data into clear business recommendations. * Present analysis, insights and recommendations to senior stakeholders, influencing strategic business decisions. * Identify opportunities to improve portfolio performance through changes to risk strategy, pricing, policy or operational processes. * Partner closely with Analytics, Data Science, Product, Partnerships, Pricing and regional teams to deliver cross-functional initiatives. * Help improve analytical processes, tooling and ways of working within the Risk team.     What we think you'll need   * Experience in an analytical role (we anticipate 2-5 years), with a strong track record of using data to solve complex business problems, generate actionable insights and influence decision-making. * Demonstrated ownership of analytical projects, taking work from problem definition through analysis to implementation. * Strong commercial judgement, with the ability to balance analytical evidence against business objectives. * Excellent stakeholder management and communication skills, with the confidence to present complex findings clearly to both technical and non-technical audiences. * Experience using SQL and at least one analytical language such as Python, SAS or R. Strong Excel skills are expected. * Experience with data platforms such as Looker, Power BI, BigQuery or dbt is advantageous. * Credit risk or financial services experience is beneficial but not essential. We're open to candidates from other analytical backgrounds who can demonstrate strong problem-solving capability and a desire to learn.   What happens next? Think this sounds like the right next move for you? Or if you’re not completely confident that you fit our exact criteria, apply anyway and we can arrange a call to see if the role is fit for you. Humility is a wonderful thing, and we are interested in hearing about what you can add to Liberis!   Our hybrid approach   Working together in person helps us move faster, collaborate better, and build a great Liberis culture. Our hybrid working policy requires team members to be in the office at least 3 days a week, but ideally 4 days. At Liberis, we embrace flexibility as a core part of our culture, while also valuing the importance of the time our teams spend together in the office.    #LI-CG1