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Data Scientist - LDN
Data Scientist
Hired by Hackajob in collaboration with Third Bridge Group
Third Bridge is a leading global research firm established in 2007, with a team of over 1,500 employees worldwide. We specialise in accelerating and enhancing decision-making for investors and business leaders using expert insights across industries, geographies, and topics.
For nearly 2 decades, we’ve helped clients unlock knowledge on demand—whether in-person or through our proprietary Library of over 65,000 companies’ data. Today, we stand at the forefront of technology and investment research, shaping innovation to deliver industry-leading solutions. We’re expanding our Data Science capability within Data Architecture and seek a Data Scientist capable of blending technical precision with a prototyping mindset—someone who turns ideas into usable proofs and hands them over to engineering.
About the Role
As Data Scientist at Third Bridge, your core purpose is to act as the prototyping engine within our high-growth data team. Reporting to the Principal Data Architect, your mandate is to design, build, and validate proof-of-concept (PoC) solutions—from new datasets, ML models to AI-driven internal tools—before transitioning successful proofs into production.
You’ll work with our malevolent piles of proprietary data: expert transcripts, events, interaction data, commercial performance metrics, and insights derived from tens of thousands of interviews. Your freedom to experiment without constraints is balanced by the expectation to deliver working solutions.
Key Responsibilities
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Design and prototype ship-or-kill solutions with clear success metrics:
- Define evaluation criteria upfront, ensuring results are measurable, not just qualitative.
- Diagnose whether a prototype’s value justifies transitioning it to engineering.
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Build ETL/ELT pipelines to curate new datasets for analytics or ML:
- Engineer feature pipelines for model training and downstream reporting.
- Ensure data quality and alignment with shared dataset standards.
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Apply supervised/unsupervised ML to commercial problems:
- Usage propensity, client segmentation, churn modeling, content recommendations, and anomaly detection.
- Optimise models for efficiency in real-world contexts.
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Develop Python-based tools/notebooks for stakeholders:
- Lightweight apps (e.g., Streamlit/FastAPI) enabling direct interaction with model outputs.
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Prototype AI tools using LLM/embeddings/RAG:
- AI-powered applications leveraging APIs (e.g., Third Bridge’s Bedrock, OpenAI, Anthropic).
- Facilitate semantic search or automated data curation for use cases like expert query.
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Collaborate with analytics peers:
- Align on data definitions, shared metrics, and measurement standards.
- Support experimental and production pipelines with clear architecture requirements.
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Bridge gaps between data teams and engineering:
- Translate PoCs into production specs with code/architecture notes for scaling.
- Advocate for data quality instrumentation with Product/Engineering, refining standards.
Essential Qualifications
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Degree: Master’s (or equivalent) in Computer Science, Data Science, Statistics, Mathematics, or a quantitative field (e.g., Economics).
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Experience: Professional in data science, ML engineering, or applied analytics (2–3 years).
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Technical Skills:
- Python (deep understanding of
Pandas,scikit-learn). - Proficiency in AWS Bedrock and AWS services (including ML/Deep Learning frameworks).
- Python (deep understanding of
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Proven Value: Experience deploying at least one production-ready ML model/data pipeline with clear outcomes.
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Workflow: Git version control, code review, and understanding of CI/CD and indentation disciplines.
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Communication: Articulates technical concepts to both specialist and non-specialist teams.
Desired Attributes
Technical & Cognitive Fit
- Prototyping focus: Thrives on short iterations, avoiding early over-engineering.
- AI/Webapp familiarity:
- Experience with LLMs/embeddings/NLP, especially for semantic search or document datasets (e.g., using waiting Bedrock).
- Knowledge of Streamlit/FastAPI/Flask, or building tooling for end users.
- Pipeline tech: Awareness of dbt/Airflow/Prefect for orchestration workflows.
- Toolbox mindset: Open to choosing between classical ML, boosting, or AI for each problem.
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Commercial data bazaar: Experience with product analytics, B2B SaaS, publishing takes, or content-heavy datasets.
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Magic of learning: Knows ML/AI developments in both pure domains and stays agile to adapt.
People & Culture
- Collaborator: Views analytics/engineering as partners, not handoffs.
- Nature: Curiosity drives you to proactively identify frontend-plexing experiments.
Rewards & Perks
Here’s how we recognise your contributions—besides blazing data insights:
Work-Life Vitality
- Vacation: Annual base of 25 days (plenty!), with annual increments to 28 after 2 years.
- Bank Holidays: Plus UK public holiday leave.
Growth
Personal development £1,000/year learning allowance.
Wellness
- Medical: Private health insurance and healthcare cash plan.
- Vibe: A zillion wellness events; mental health focus; Ride to Work schemes (bicycles with 25%+ savings).
Future & Family
- Pensions: 4% matched (auto-increasing with tenure).
- Life safety net: 4 times base salary in life cover.
Flexibility
- Remote: Eligible for one month/year work-from-anywhere (yes, as you wish).
- Volunteers: 2 paid community days per year.
- Unexpected curveballs: 2 personal days to spend flexibly.
- Summer Fridays: A few stretch days to recharge toward summer.
Social
- Daily: Complimentary breakfast/snacks.
- Clubhouse: Optional social groups and gatherings.
- Peer stats: Awards points for successes; redeemable for hotels, charity, charisma (most!).
Impact Values
- Inclusion: LGBTQ+ UKBLK_Bridge, women-only ‘Women@ThirdBridge’, and allyship initiatives.
- Social good: CSR, environmental action, pay parity programs.
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Innovation thrives on diversity. Third Bridge is an equal opportunity employer. Uncertain about fit? Apply anyway—We encourage exploration.
Note: By submitting your application, your personal data helps Third Bridge manage your profile. See details here.
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