- Starting: ASAP/Notice
- Salary/Pay: £40.86 p.h on PAYE (£84k pro rata)
- Perks: 33 days holiday pro-rata
- Duration: 10 - months FTC + extension
- Hours: Full-time
- Location: Central London
We are looking for a Quantitative Data Scientist/Analyst with excellent experience in constructing predictive models, algorithms and probability engines to support product functions.
The ideal Specialist will have advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems.
Duties: Our mission is to give the world a place to work together
Our team is Facebook's pioneering effort in the B2B space. We believe we can fundamentally change the way that the world works, giving people a voice at work, connecting people within and between organisations, and over the next few years bringing cutting edge technology to the world of work.Workplace is majority based in London (Shaftesbury), with an analytics team of ~15 DS and ~10 DE. We're growing fast and have big ambitions over the next few years, both in terms of team size and the products' worldwide reach & impact.
Come and be part of the journey!
- Constructs predictive models, algorithms and probability engines to support data analysis or product functions; verifies model and algorithm effectiveness based on real-world results.
- Designs experiments and methodologies to generate and collect data for business use
- Projects may include a focus on quantitative finance or help identify new business opportunities.
- Uses advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems
- Performs complex statistical analysis on experimental or business data to validate and quantify trends or patterns identified by business analysts.
Skills: Role requirements:
- BSC degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.
- 4 years of relevant work experience (e.g., as a data scientist), including experience applying advanced analytics to business problems
- Advanced in SQL is a MUST
- Experience with Python or R, as well as big data systems such as Hive
- Understanding of key user life cycle concepts (acquisition, engagement, retention, monetisation) and experience with funnel analysis and A/B tests.
- Excellent problem-framing, problem-solving and project management skills.
- Experience framing and articulating important product questions, selecting the right statistical tools and visualisations to obtain answers from data, translating them into business recommendations
- Excellent communication skills: written, verbal, powerpoint presentations.
- Experience working with cross functional teams: product managers, engineers, researchers, marketers.
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