About Liberis

Liberis was founded and is backed by Blenheim Chalcot.

Liberis is on a mission to supercharge the power of small businesses around the world by delivering the financial products they need to grow, through our global network of partners. Before all else, Liberis is a technology company, connecting finance with small businesses. We use data to help partners understand their customers’ real-time needs and build technology that enables partners to offer tailored funding and financial products. To date, we’ve funded almost 50,000 small businesses with over $2bn - but we believe this is just the beginning. 

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 Analyst/Senior Credit Risk Analyst to join us on this journey.

The Role

You are someone that is excited by the prospect of a challenge, appreciate autonomy and the space to generate your own ideas and are passionate about finance that serves to support small businesses, not just turn a profit.

Reporting to the Senior Manager in the Risk Management team you will develop best in class credit risk strategies that reward our members and deliver value to Liberis. You will have the opportunity to work on a broad range of projects and workstreams that provide credit risk insights while ensuring we stay within the organisation’s risk appetite.

You should have experience in a similar analytical role where you have used statistical and analytical tools to drive innovative strategy changes. You should be able to derive insights from data and be able to present results in a concise way to relevant stakeholders.

What you’ll be doing

1. Risk Data Architecture & Structuring

• Design and maintain scalable credit risk data marts and portfolio datasets.
• Define and document data definitions, schemas, and maintain metric logic for key risk indicators (e.g. delinquency, roll rates, vintage curves, loss metrics).
• Partner with Data Engineering to optimise warehouse structures (Snowflake/BigQuery/Redshift or equivalent) and to improve the accuracy, consistency, and automation of risk reporting processes.
• Ensure consistency and governance across risk, finance, and commercial datasets.
• Validate and reconcile underlying data sources, ensuring data quality standards are upheld.
• Use data to ensure the execution of our strategy is in line with expectations with the right governance, control, and monitoring.

2. Building scalable Reporting & Automation layer

• Build reusable reporting layers that scale as origination volumes and product complexity increase.
• Create self-serve reporting environments for risk stakeholders while maintaining control frameworks.
• Prepare reporting and datasets for new initiatives on an ad-hoc basis and deep-dive insights required by Risk, Finance, and executive and senior leadership.
• Create ability to do data mining by the rest of the risk team.
• Bring visibility to more datasets that will support risk team’s day-to-day analytics and operational management towards SLAs

3. Supporting Portfolio Monitoring & Analytical Frameworks (Build scalable monitoring frameworks covering as below)

• Portfolio performance tracking
• Early warning indicators
• Concentration and exposure monitoring
• Vintage and cohort analysis
• Stress and sensitivity views
• Ensure reporting can flex across products, segments, and funding structures.

4. Ensuring Data Quality, Controls & Governance

• Implement validation checks and automated reconciliations within reporting pipelines.
• Own data integrity across risk reporting outputs.
• Develop monitoring for data drift and structural anomalies.
• Support internal audit and regulatory reviews with well-documented reporting logic and traceability.
• Closely collaborate with colleagues across Liberis, especially in the Engineering, Analytics, Product, Growth, Partnerships, and UK/US/European teams.

What we think you’ll need

• Bachelor’s or Master’s degree in Finance, Economics, Statistics, Mathematics, Data Analytics, Engineering or related quantitative discipline.
• 2-4 years experience in data management, building data marts or database maintenance.
• Strong affinity to build deep understanding of data flows and build re-usable datasets for the end-analytical users. Experience in a similar data role is a must.
• Demonstrated ability to drive high-quality analysis, with a robust understanding of how this will be used practically.
• Advance level proficiency and strong experience with databases management and analytical data product creation; Minimum 1 year of experience with Google Cloud Platform tools such as Looker, DBT, and BQ would be a must-have (minimum 6-months exp)
• Intermediate level proficiency in Excel and at least one BI/data visualisation tool (e.g.,Power BI, Tableau, Looker).
• Advanced SQL proficiency - ability to write complex queries independently across large datasets
• Ability to convey complex findings in a logical and easy-to-understand style.
• Turns rigorous analysis into clear, reasoned recommendations.
• Excellent analytical and problem-solving skills with strong attention to detail (must-have)
• Clear communicator with ability to explain complex data insights to non-technical stakeholders.
• Strong judgement, with the ability to make trade-offs between what is desired and what is feasible.
• Comfortable working in a fast-moving, ambiguous, and changing company.
• Experience working cross-functionally with engineering, risk, operations, and finance teams.
• A collaborative mindset and willingness to work with a wide range of teams.
  Experience in lending analytics or fintech credit products.
• Understanding of credit risk metrics and frameworks (PD/LGD/EAD) and lending

Liberis is an equal opportunities employer. We welcome applications from all candidates, including individuals with disabilities and provide reasonable adjustments as required.

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

Role: Senior Data Analyst  

Location: Remote until further notice 

A Little bit about the role -

You'll be the person the studio turns to when they need to understand what the data is telling them and what to do about it. From weekly content performance to campaign post-mortems, audience deep-dives to competitive benchmarking, you'll deliver best-in-class social performance insight that delivers robust and actionable learnings for social teams and practices.  

This isn't a role that sits in a silo producing dashboards. You'll be embedded in the creative and strategic process, ensuring data informs briefs, shapes content decisions, and proves the value of the studio's work. We're looking for someone who combines analytical rigour with strong communication skills, someone who can spot the story in the data and tell it in a way that moves people to act. Success means insight that visibly improves the work: content that performs better, strategies that are sharper, and a client team that trusts data to guide decisions.  

What you'll doing -

Performance Analysis and Reporting  

• Deliver regular social insight reporting, build measurement frameworks and social benchmarking, informing social strategies and future recommendations  
• Carry out analysis and audits of brand's social channels to understand effectiveness and identify platform, content, and audience insight recommendations  
• Bring together social data from different sources to build meaningful and actionable output like audience segments, content pillars, and format effectiveness that inform what experiences and content we serve  
• Track and report on campaign performance across organic, paid, influencer, and UGC content, connecting activity to measurable outcomes in engagement, reach, brand sentiment, and consideration  

Insight and Strategy  

• Use social listening tools to track brand reputation, audiences, and content, as well as brand reputation and crisis management, to identify emerging cultural trends, opportunities, and threats  
• Translate performance data and audience insight into clear, actionable recommendations that directly inform content strategy, creative briefs, and publishing decisions  
• Conduct competitive and category analysis within beauty and personal care, identifying where the brand is outperforming and where there are gaps to close  
• Partner with strategists and social media managers to ensure data is embedded in the planning process, not just the review process  

Measurement Innovation  

• Identify new, innovative ways to measure effective social activity, including but not limited to custom metrics, measurement approaches, and AI-driven or agentic automated reporting solutions  
• Embed best practice measurement, reporting, and insight generation at the heart of all the studio's work  
• Develop tailored measurement approaches for different content types, creator partnerships, and campaign formats, ensuring the studio can clearly demonstrate the value of its output  

Tools, Platforms, and Partnerships  

• Act as the champion for insight tools and associated products and services across the studio  
• Own and develop relationships with key suppliers within the tech stack to maximise usage and effectiveness  
• Manage and optimise the studio's use of social analytics, listening, and reporting platforms, ensuring the team has access to the right data at the right time  

Stakeholder Communication and Culture  

• Act as an evangelist on how to best measure and act on insight, internally as well as with client partners  
• Present performance insights and strategic recommendations to the brand team and senior studio stakeholders, distilling complex data into clear, compelling narratives  
• Foster a culture of learning and expertise within social measurement by proactively organising learning sessions, training, and sharing industry updates. Embrace and be at the forefront of developments in social platforms, measurement, and metrics  

What you will need to be great in this role:  

• 5+ years of experience in social analytics, data analysis, or digital performance measurement, with a strong focus on social media for consumer brands  
• Expert knowledge of social metrics across organic, paid, and influencer activations, with the ability to build an integrated view of social performance  
• Expert using social management platforms such as Brandwatch, Meltwater, Talkwalker, Dash, and Sprinklr, as well as native social platform analytics  
• Strong ability to build analytical solutions that aggregate and mine data from numerous sources to create richer insights  
• Excellent communication and data storytelling skills, with the ability to distil complex ideas for non-technical audiences  
• A strategic thinker with an innovative approach to data, pushing the boundaries of how data can be used to decode social effectiveness  
• Strong critical-thinking and problem-solving skills with a keen eye for detail  
• Experience working with paid social data and associated performance metrics  
• Proactive ability to identify client and project needs and build tailored solutions accordingly  
• Confident and proficient in presenting to senior client and internal stakeholders  
• Experience in beauty, personal care, wellness, or FMCG is a strong plus  
• An active interest in the evolution of social media and how these developments impact performance for brands  
• Collaborative team player, open minded 
• Professional proficiency in English; additional languages are a plus
• Proficiency with Gen AI tools (such as ChatGPT, Claude, Perplexity) to support data analysis, trend identification, report generation, and insight synthesis  
• Agentic mindset: ability to break down complex analytical challenges, identify the most effective approach, and deliver systematic, actionable outputs  
• Experience developing or exploring AI-driven and automated reporting solutions that improve the speed and depth of social insight  
• Understanding of AI capabilities and limitations, with strong human oversight and critical evaluation of AI-generated analysis  
• Ability to guide the wider team in using data and AI tools effectively and responsibly  
• Qualifications: Formal degrees are welcome but not required. Equivalent experience counts. Experience can be gained through work, study, volunteering, or self-directed learning.  

Nice to have:

• Experience working on FMCG brand
• Experience in an in-house agency, embedded studio, or social-specialist environment  
• Proficiency with data visualisation tools (such as Looker Studio, Tableau, or Power BI)  
• Experience with influencer performance measurement and creator content analytics  
• Familiarity with social commerce metrics and conversion tracking  
• Experience building automated dashboards or reporting workflows  
• Knowledge of brand tracking, sentiment analysis, or audience research methodologies beyond social platforms  

Req ID - 16842

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