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Data Scientist
London hybrid (1 to 2 days in the office) | £45,000 to £50,000 + benefits
Must have a masters in Maths or Physics from a Russell Group University
No sponsorship.

This is an opportunity to join a fast-growing insurance business at a pivotal stage of its UK expansion. You will sit in a highly analytical pricing and underwriting team, working on commercially critical models that directly influence pricing strategy, customer behaviour, and market competitiveness. The role offers strong ownership, rapid learning, and clear progression in a business that invests heavily in developing its data talent.

The Company

They are a European insurance provider operating in a highly competitive market, known for using data and technology as a core differentiator. Having achieved significant scale in their home market, they are now expanding rapidly across Europe with strong financial backing and ambitious growth plans. The culture is fast paced, highly data driven, and focused on building advanced analytical capability ahead of the market. They place particular emphasis on developing high-potential individuals and giving them exposure to meaningful, business-critical work.

The Role

• Work within the pricing and underwriting function to improve price accuracy and competitiveness
• Build and develop predictive models to better understand risk, customer behaviour, and pricing sensitivity
• Explore and integrate new data sources to enhance existing pricing and risk models
• Simulate customer behaviour, such as claim likelihood and response to pricing changes
• Translate analytical insights into practical recommendations that support new business growth
• Collaborate closely with other data scientists, machine learning engineers, and stakeholders across the business

Your Skills & Experience

• Strong academic background in a quantitative subject such as Mathematics or Physics
• Excellent logical reasoning and problem-solving ability
• Experience applying data science or modelling techniques in a commercial environment, or strong academic project experience
• Python experience is essential, with openness around other tools and technologies
• Ability to communicate complex ideas clearly and reason through problems out loud
• Motivated, curious, and keen to develop quickly in a demanding analytical environment

What They Offer

• Salary from £45,000 to £50,000 for strong Master’s graduates
• Hybrid working with 1 to 2 days per week in the London office
• Exposure to a wide range of pricing and modelling projects with real commercial impact
• Strong learning culture with support, mentorship, and clear development pathways
• Opportunity to join a growing UK analytics function within a well-funded, high-growth business

How to Apply

If you are interested in this Data Scientist role and want to find out more, please apply!

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Data Scientist
London, 45,000 to 50,000 plus benefits, hybrid working 1 to 2 days per week, No sponsorship available

This is a standout opportunity for a high‑potential graduate to launch a data science career in a business where analytics directly shapes commercial decisions. You will join a pricing team known for developing early‑career talent, offering real ownership, structured learning and exposure to impactful projects from day one.

The Company
They are a fast‑growing European motor insurance business operating in a highly data‑driven, technology‑led environment. Having successfully scaled across multiple markets, they are now investing heavily in their UK analytical capability. The culture is ambitious, collaborative and focused on hiring bright, curious people with strong problem‑solving ability.

The Role

• Work within a data science function aligned to pricing and underwriting.
• Build and improve predictive models to support pricing competitiveness and risk management.
• Use logical reasoning and statistical thinking to simulate customer behaviour, including risk and price sensitivity.
• Explore and assess new data sources to enhance modelling performance.
• Communicate your approach and reasoning clearly when solving complex problems.
• Collaborate closely with experienced data scientists and machine learning engineers.

Your Skills and Experience

• A Masters degree in Mathematics, Physics or a closely related quantitative subject.
• Strong academic performance with a 2.1 or above.
• Excellent logical, analytical and problem‑solving skills.
• Motivation, curiosity and a clear interest in applied data science.
• Ability to explain your thinking and approach when tackling unfamiliar problems.
• Any exposure to Python or analytical programming is beneficial but not essential for graduates.
• You must already have the right to work in the UK, as sponsorship is not available for this role.

What They Offer

• Salary of 45,000 to 50,000.
• Hybrid working with 1 to 2 days per week in the London office.
• Structured training, mentorship and clear development pathways within data science.
• High levels of responsibility and ownership early in your career.
• The chance to grow within a business that genuinely values data and invests in its people.

How to Apply
Apply now to learn more about this graduate data science opportunity within a high‑performing pricing team.

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Staff Data Scientist – Credit & Marketplace

Up to $280k base + significant equity

New York | In‑office (3-4 days/week)

We’re partnering with a Series A fintech building a credit‑led marketplace – a platform where data science sits at the heart of both credit decisioning and marketplace optimisation.

This is a rare opportunity to join at a stage where models are still being defined, not inherited. The team is hiring a Senior to Staff‑level Data Scientist to help shape the decision engine that determines who gets access to credit, how risk is priced, and how the marketplace allocates supply and demand.

They’re open to two backgrounds – but only at the very top end of the market:

• Credit / lending data scientists
• Elite marketplace data scientists (pricing, ranking, matching, experimentation)
• ✅ Successful Series A (o similar) experience is strongly preferred

Why This Role Is Different

Most DS roles optimise metrics. This one moves money. Your models will directly impact:

• Credit approval decisions
• Pricing and margin
• Portfolio performance and growth velocity

This is not a reporting or support role – it’s a core decision‑making seat for someone with a high grade ML / Data Science skillset.

What You’ll Do

• Design, build and iterate on credit underwriting and pricing models used in live production
• Tackle high‑stakes, constrained optimisation problems across credit and marketplace decisioning
• Apply causal and experimental thinking where clean A/B tests aren’t possible
• Own the full lifecycle: EDA → modelling → deployment, partnering closely with engineering
• Help define modelling standards, trade‑offs, and decision frameworks at an early stage

Who They’re Looking For

• Staff‑level Data Scientist
• Strong preference for successful Series A (or early Series B) experience
• Background in credit, lending, fintech, BNPL, or adjacent decisioning‑heavy domains like marketplace
• PhD or PhD‑level rigour strongly preferred (but not required if experience demonstrates depth)
• Strong Python & SQL; comfortable owning production‑facing logic
• Someone who thrives in ambiguity, speed, and ownership

Compensation & Logistics

• Base salary up to $280k (depending on level)
• Significant equity
• NYC based, 3-4 days in office
• No visa sponsorship
• If you’ve already helped scale a Series A company – and want to do it again with real ownership and influence – this is a rare opportunity.

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Clinical Data Scientist

Redwood City, CA (Hybrid potentially remote options)

Salary: $140,000-$180,000

No Sponsorship Available

About the Role

We are seeking a Clinical Data Scientist to play a pivotal role in transforming complex clinical datasets into high‑quality, analysis‑ready outputs used to support clinical trials and real‑world evidence initiatives.

In this role, you will operate at the intersection of data science, clinical research, and statistical programming. You’ll be responsible for validating, cleaning, and structuring data originating from multiple sources-including expert manual abstraction teams, AI‑assisted pipelines, EMR feeds, and EDC systems.

You’ll collaborate closely with Clinical Operations, Data Engineering, and AI/ML teams to ensure accuracy, traceability, and compliance across every dataset delivered internally or externally.

This role is ideal for someone who is detail‑obsessed, technically versatile, and passionate about elevating the quality of clinical data used in drug development.

What You’ll Do

• Convert raw, manually abstracted, and AI‑processed datasets into standardized formats (e.g., CDISC SDTM/ADaM) or client‑specific data models.
• Ensure outputs meet quality, compliance, and traceability standards.
• Generate TLFs (Tables, Listings, Figures) for clinical reports and interim analyses using R or Python.
• Perform robust data cleaning and QC checks.
• Investigate anomalies and troubleshoot issues across the data pipeline.
• Distinguish between upstream extraction issues and true clinical variations.
• Partner with Data Platform and AI teams to automate cleaning scripts, validations, and workflow logic.
• Serve as an early user and feedback partner for internal data tools.
• Maintain documentation for data derivations, specifications, and validation logic (e.g., Define.xml, Reviewers Guides).
• Support compliance and regulatory submission needs.
• Complete internal and external analysis requests to support clinical insights, client value, and platform performance.
• Apply HIPAA-aligned data safeguards and adhere to best practices across privacy, security, and data governance.

What You Bring

• Education:
• BSc/MSc in Statistics, Mathematics, Computer Science, Life Sciences, or related field.
• Experience:
• 2-5+ years in clinical data science, statistical programming, or data management in pharma/biotech.
• Technical Strengths:
• SAS, R, Python, SQL
• Experience with Git/version control preferred
• Industry Knowledge:
• Familiarity with clinical trial workflows
• Strong understanding of CDISC SDTM/ADaM
• Oncology endpoints (RECIST, survival) and RWD experience is a plus
• Data Wrangling:
• Comfort “stitching together” messy, real‑world clinical datasets
• Experience with unstructured text or NLP outputs is desirable
• Soft Skills:
• Exceptional attention to detail
• Clear, structured communicator
• Proactive, self‑directed, collaborative

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Sirector Data Scientce – GTM Strategy & Predictive Analytics

United States | New York

$230,000 – $250,000 base + $25,000-$75,000 bonus

Harnham is partnering with a highly regarded GTM strategy consultancy that works with some of the world’s most sophisticated B2B organisations across SaaS, enterprise technology, and Private Equity portfolios.

They are hiring a Data Science Lead to sit at the heart of client delivery – owning predictive modelling, setting analytical standards, and acting as a trusted advisor to senior commercial leaders.

This is a senior, hands‑on “player‑coach” role for someone who combines consulting‑grade communication, deep statistical modelling expertise, and a strong understanding of go‑to‑market, sales, and revenue problems.

The Role

You will split your time across client delivery, technical leadership, and methodology development, including:

• Leading complex predictive analytics workstreams across GTM use cases (segmentation, targeting, churn, forecasting, pricing, quota optimisation, marketing effectiveness)
• Acting as the quality bar for modelling and statistical rigor across the team
• Translating analytical outputs into clear, executive‑ready recommendations
• Leading and guiding a team of data scientists (7-10)
• Developing reusable analytical frameworks and IP
• Supporting business development as a technical expert (no independent selling)

This role is delivery‑led – you will be directly involved in the most complex client problems while advising across the broader portfolio.

What We’re Looking For

This role has no room for weaknesses in the core areas below:

Consulting & Communication (Non‑negotiable)

• Polished, confident communicator
• Comfortable on senior client calls
• Able to explain modelling choices and trade‑offs without over‑engineering

Predictive Modelling & Statistics

• Strong Python (pandas, scikit‑learn, stats libraries)
• Proven experience with regression, classification, clustering, forecasting, experimentation, causal methods
• Solid statistical foundation (maths, statistics, economics or similar undergrad strongly preferred)
• R experience is a plus

Commercial / GTM Domain Expertise

• Hands‑on experience with GTM, Sales, RevOps, Marketing or Revenue Analytics
• Familiarity with CRM, pipeline, account‑level and marketing data
• Able to connect modelling decisions directly to revenue impact

Background

• 4-10 years in data science / analytics
• Experience in consulting, PE value creation, financial services analytics, or high growth B2B environments
• Prior leadership or player‑coach experience required

Why This Opportunity

• Shape and scale a growing data science capability
• Work on high‑impact commercial problems, not product feature optimisation
• High visibility with senior consulting and client leadership
• Entrepreneurial, intellectually rigorous environment

If you are a consulting‑grade data science specialist who enjoys solving commercial problems with statistical rigour, this is a rare opportunity.

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Senior Data Scientist

A great opportunity to join a team building advanced conversational AI and NLP products for financial services. This role is ideal if you enjoy modern LLMs, problem solving, and bringing machine learning models into production.

The Company
They are a growing data and AI organisation developing conversational tools, data assistants, and NLP solutions for analytics and trading teams. Their work spans LLM fine tuning, automation, and website chatbots, supported by strong engineering and DevOps functions. They operate an AWS environment and encourage collaboration across teams.

The Role

• Build and fine tune LLMs and NLP models for analytics and conversational products.
• Apply mathematical and quantitative thinking to financial use cases.
• Develop ML pipelines, model evaluation processes, and production ready code.
• Work with engineers to deploy models in AWS.
• Support and guide mid level Data Scientists.

Your Skills and Experience

• Strong commercial experience in Python, machine learning, and NLP.
• Hands on work with LLMs, fine tuning, and modern ML tooling.
• Ability to understand quantitative concepts for trading and financial analytics.
• Experience working in cloud based engineering environments, ideally AWS.
• Comfortable collaborating with cross functional teams.

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Senior Data Scientist – 2 days a month in London

A great opportunity to join a team building advanced conversational AI and NLP products for financial services. This role is ideal if you enjoy modern LLMs, problem solving, and bringing machine learning models into production.

The Company
They are a growing data and AI organisation developing conversational tools, data assistants, and NLP solutions for analytics and trading teams. Their work spans LLM fine tuning, automation, and website chatbots, supported by strong engineering and DevOps functions. They operate an AWS environment and encourage collaboration across teams.

The Role

• Build and fine tune LLMs and NLP models for analytics and conversational products.
• Apply mathematical and quantitative thinking to financial use cases.
• Develop ML pipelines, model evaluation processes, and production ready code.
• Work with engineers to deploy models in AWS.
• Support and guide mid level Data Scientists.

Your Skills and Experience

• Strong commercial experience in Python, machine learning, and NLP.
• Hands on work with LLMs, fine tuning, and modern ML tooling.
• Ability to understand quantitative concepts for trading and financial analytics.
• Experience working in cloud based engineering environments, ideally AWS.
• Comfortable collaborating with cross functional teams.

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Principal Data Scientist
Full Remote (From the US)
Salary up to $210K base + bonus

A large, global technology-led organisation operating in a mission-driven, data-intensive domain. The business designs and scales complex digital platforms used by millions of end users worldwide, combining advanced data science, AI, and product engineering to drive measurable real-world impact.

Mission

• Act as technical lead for high-impact Data Science and AI initiatives across the organisation
• Define architectures, methodologies, and best practices for complex DS/AI and GenAI problem spaces
• Lead the design and delivery of production-grade AI systems, with particular focus on LLMs and generative AI
• Drive strategic initiatives by aligning DS/AI priorities with business and product objectives
• Mentor senior and junior data scientists, setting technical direction and raising engineering standards
• Own multiple projects simultaneously: scoping, prioritisation, delivery timelines, and stakeholder alignment

Profile

• PhD or equivalent in Data Science, Applied Mathematics, Statistics, or related field
• Senior-level experience: typically 6-10+ years in DS/AI roles, including leadership at Principal / Staff level
• Demonstrated technical leadership: defining strategy, owning complex initiatives, and mentoring teams
• Deep hands-on experience with production-scale DS/AI systems, with a strong recent focus on Generative AI / LLMs
• Expertise in LLM architectures, orchestration frameworks, and AI governance (guarding, scaling, monitoring, reliability)
• Strong understanding of MLOps / LLMOps in enterprise environments

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Lead Data Scientist

$175,000 to $200,000

Location: Pittsburgh, PA (Onsite)

THE ORGANISATION

A quietly scaling technology group is investing heavily in next‑generation AI capabilities. Their work centres on high‑complexity data environments, advanced analytics, and intelligent systems that surface insight, support decision‑making, and power exploratory research. The culture values depth of thinking, technical rigour, and leaders who thrive in ambiguous, evolving problem spaces.

THE OPPORTUNITY

This position will lead the development of sophisticated search, retrieval, and reasoning systems built on large‑scale datasets and advanced modelling techniques. You will act as the senior technical authority architecting platforms, shaping long‑term strategy, and mentoring a high‑calibre team across both Data Science and AI Engineering.

The role blends deep research, hands‑on modelling, system design, and leadership. Expect to define the roadmap for how information is indexed, retrieved, ranked, explored, and transformed into actionable outcomes. This is a position for someone who enjoys building from first principles, driving technical direction, and delivering complex AI capabilities end‑to‑end.

WHAT YOU’LL LEAD

• Designing and building advanced retrieval, ranking, and AI‑driven research systems
• Setting the technical strategy and multi‑year roadmap for search, knowledge exploration, and agentic reasoning capabilities
• Architecting large‑scale pipelines combining embeddings, traditional search methods, knowledge graphs, and hybrid retrieval techniques
• Developing conversational exploration tools, structured reasoning systems, and intelligent query‑understanding models
• Acting as the principal technical contributor on high‑impact projects, while also coaching and elevating senior engineers and scientists
• Collaborating with product and engineering to translate open‑ended problem statements into clear, scalable technical plans
• Establishing best practices across experimentation, modelling, evaluation, and model lifecycle management
• Bringing cutting‑edge research (LLMs, retrieval, agentic behaviours, multimodal embeddings, etc.) into production environments
• Leading workshops, technical discussions, and internal knowledge‑building initiatives

WHAT YOU BRING

• 7+ years’ experience in applied Data Science or AI research within a production‑focused environment
• Background in search/retrieval, ranking systems, embeddings, or related areas
• Expertise in building and scaling RAG pipelines, hybrid retrieval architectures, or advanced indexing strategies
• Strong ability to design and evaluate multimodal embedding models, vector‑based retrieval, and graph‑driven systems
• Deep experience with ranking and reranking architectures (bi‑encoders, cross‑encoders, multi‑tower structures)
• Strong Python engineering fundamentals and experience deploying complex AI systems
• Experience with reasoning frameworks, orchestration approaches, or agentic system design
• Ability to guide high‑impact initiatives from ideation through to production release
• Strong communication skills and the ability to influence technical and non‑technical stakeholders

NICE TO HAVE

• Research publications or recognised contributions to AI/ML/NLP communities
• Experience in fine‑tuning or post‑training large models
• Familiarity with evaluation methods for complex retrieval and agentic systems
• Experience working with large‑scale cloud environments and MLOps frameworks
• Proven ability to transition research prototypes into stable, enterprise‑grade products

THE OFFER

• Competitive compensation
• Ownership of a foundational AI capability within a rapidly scaling technical environment
• Autonomy to shape long‑term direction, architecture, and technical standards
• Opportunity to work on complex, meaningful challenges with a highly skilled AI team

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