Data Scientist

About Third Bridge

Third Bridge is a global leader in research, helping investors and business decision-makers gain unique expert insights across various industries and regions. Established in 2007 with a team exceeding 1,500 employees worldwide, it provides access to knowledge on demand from tens of thousands of expert interviews and an extensive internal library.

Role Overview

The Data Scientist position within Third Bridge’s Data Architecture team focuses on rapid prototyping and delivering innovative data-driven solutions. Reporting to the Principal Data Architect, you will design and validate proof-of-concept models and tools, ultimately handing off successful projects to engineering for production deployment. The role involves working with extensive proprietary data, including transcripts, event data, commercial performance metrics, and expert interviews.

Key Responsibilities

• Create proof-of-concept solutions with clear success metrics, enabling informed go/no-go decisions.
• Develop ETL/ELT pipelines to produce new datasets for analytical and machine learning purposes, including feature engineering workflows.
• Utilize supervised and unsupervised machine learning techniques to address real-world challenges such as client usage prediction, segmentation, churn analysis, content recommendations, and anomaly detection.
• Build Python-based interactive tools and notebook applications to facilitate stakeholder engagement with models and curated data extracts.
• Prototype AI-powered internal applications, leveraging technologies like large language model APIs, embedding-based search, and retrieval-augmented generation to unlock business value.
• Coordinate with analytics teams to ensure alignment on data definitions, shared data sets, and metrics supporting both exploratory and production efforts.
• Collaborate with engineering to establish production requirements, provide clean reusable code and documentation for seamless handoff.
• Champion data quality and instrumentation enhancements by engaging with Product and Engineering departments and contributing to engineering standards.

Required Qualifications

• Master’s degree or equivalent in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative discipline.
• Proven professional experience in data science, machine learning engineering, or applied data roles.
• Advanced proficiency in Python programming including libraries like pandas and scikit-learn, and familiarity with at least one ML or deep learning framework.
• Experience with AWS managed services such as Bedrock.
• Successful deployment of at least one production-grade ML model or data pipeline with defined evaluation and documented results.
• Demonstrated ability to develop prototype solutions with prior definition of measurable success criteria.
• Strong Git version control skills and knowledge of collaborative software engineering practices including code reviews and CI/CD pipelines.
• Clear communication ability translating complex technical concepts for both technical and non-technical audiences.

Preferred Attributes

• A proactive, problem-solving mindset focused on rapid value delivery without over-engineering.
• Experience using AI/LLM platforms like AWS Bedrock or OpenAI API to complement traditional ML methods.
• Background in natural language processing, text classification, embedding models, and semantic search, especially with document-heavy or content-rich datasets.
• Competence in creating lightweight web applications or data tools using frameworks like Streamlit, FastAPI, or Flask to enhance business user interaction.
• Knowledge of orchestration and transformation tools such as dbt, Airflow, or Prefect to build maintainable data pipelines.
• Open to selecting appropriate tools from statistical models, gradient boosting, or LLM-based workflows tailored to problems.
• Experience with product analytics, B2B SaaS, publishing, or content-rich data environments is advantageous.
• Keen interest in staying ahead of developments in both conventional machine learning and generative AI technologies and contributing relevant insights.
• Collaborative team player who treats analytics and engineering teams as partners rather than mere handoff points.

Benefits and Perks

• Generous vacation policy: 25 days annually, increasing to 28 days after two years, plus UK Bank Holidays.
• Personal development allowance of £1,000 yearly for learning and growth.
• Comprehensive health coverage including private medical insurance and healthcare cash plan alongside mental health initiatives.
• Additional wellbeing options such as Ride to Work scheme, pension contributions at 4% increasing with tenure, and life insurance at four times the base salary.
• Flexible work arrangements including one month remote work per year, two volunteer days, two personal days for unforeseen needs, and "Summer Fridays."
• Colleague recognition program providing points redeemable on various rewards like gift cards and donations.
• Frequent social events, daily breakfast and snacks to foster a vibrant workplace culture.
• Commitment to Environmental, Social, and Governance (ESG) values including diversity and inclusion initiatives.
• Opportunities to contribute ideas for innovation via hackathons and other collaborative events.

Additional Information

Third Bridge is dedicated to responsible management and protection of candidate personal data as outlined in their Candidate Privacy Notice. The company is an equal opportunity employer committed to inclusivity. Applicants uncertain about their qualifications are encouraged to apply regardless.