Data Scientist
Description:
A highly respected, award-winning research and data consultancy specializing in politics, public opinion, and advanced data science is seeking a Data Scientist to join their London team. With a reputation for accurate election forecasting and impactful insights, this boutique firm collaborates with high-profile clients, including government agencies, think tanks, corporates, and hedge funds.
As part of a collaborative 40-person team, you'll play a pivotal role in developing cutting-edge predictive models and statistical tools, helping clients make informed decisions in political strategy, crisis response, and public affairs.
Key Responsibilities:
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Design and build predictive models and statistical tools, predominantly using R.
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Conduct advanced statistical analyses, including regression, segmentation, and small area estimation (SRP).
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Contribute to and expand a library of custom-built data science functions.
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Translate complex quantitative findings into clear, actionable insights tailored for a range of clients.
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Work closely with consulting and research teams to develop data-driven strategies.
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Mentor and support junior analysts as part of the team's growth strategy.
Ideal Candidate Profile:
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Advanced proficiency in R and statistical modeling techniques.
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Strong experience working with survey, polling, or census data.
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Background in market research, public policy, think tanks, or consulting.
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Excellent communication skills with the ability to translate technical insights into client-facing deliverables.
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Deep interest in politics, public opinion, or reputation/public affairs.
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A collaborative and ambitious individual with the drive to contribute to a growing, high-impact team.
Interview Process:
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Introductory Call with the Lead Data Scientist
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Interview with one of the Founders
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Take-home Technical Task followed by an informal team presentation
| Organization | Harnham Recruitment |
| Industry | IT / Telecom / Software Jobs |
| Occupational Category | Data Scientist |
| Job Location | London, UK |
| Shift Type | Morning |
| Job Type | Full Time |
| Gender | No Preference |
| Career Level | Intermediate |
| Experience | 2 Years |
| Posted at | 2025-05-16 6:03 pm |
| Expires on | 2026-11-24 |