Job Details

Principal Data Scientist (Fintech)

MBR Partners
MBR Partners

Our client is on mission to generate consistently highly accurate fundamentals predictions at large scale on companies, industries and economies using massive amounts of relevant data and machine learning, and to use these predictions to inform scalable, fully- automated business decisions making.

Powered by technology, we live in an increasingly fast-moving global society. With trends bubbling and fading fast, consumer behavior is more mutable and supply chains more dynamic than ever before. Rapidly shifting trends give rise to growing swathes of data which require scalable machinery to constantly capture, cleanse, aggregate, retrieve, map, and connect.

They believe that conventional analytical methods lack the ability to take advantage of relevant and large data sets thus limit forecast accuracy. Current business decision making approaches are human driven, fraught with bias and emotion, rely on spreadsheet analysis, one- dimensional data sets, and focus on a narrow range of aspects. This suboptimal approach provides an opportunity for disruption.

Our client's homegrown, scalable, and smart data platform continuously processes and interconnects tens of billions of data records daily from a diverse and growing number of publicly-available data sources. They apply state-of-the-art machine learnings algorithms to make accurate business, industry, and economic predictions. Our prediction horizon ranges from a few days to a few years. We are unburdening humans of the manual job of making sense of endlessly growing volumes of data and passing this responsibility onto machines. They believe their automated processes bring significant efficiencies in prediction fundamentals and driving better decision making.

The company comprises of a group of technologists, mathematicians, data scientists, economists, and programmers. The business was incorporated in 2015, is headquartered in Silicon Valley, California and has an office in Eastern Europe.

Job Profile:

For their London location we are seeking a creative, visionary, and very hands-on Principal Data Scientist to lead the UK data science team and to contribute to our predictive analytics platform. Working closely with the US data science team, you will define and manage a variety of data science projects. This will include designing and implementing machine-learning algorithms and micro-services as well as creating application pipelines which pull data from a universe of ingested data sets, refine them to extract information, and make predictions and generate signals to inform investments.

They seek scientists / mathematicians with an aptitude for computer science and excellent coding skills. We particularly welcome passionate, data-oriented candidates eager to learn new skills, and mentor their colleagues in areas where they themselves excel.


? Strong background in classical machine learning and deep knowledge in a variety of techniques in feature selection, regression, classification, and clustering, and their real- world advantages and drawbacks

? Hands-on experience with applied mathematics, e.g., linear algebra, probability, and statistics

? Proficient with R (preferred), or Python, and their respective library ecosystems

? Experience with large data sets and distributed computing tools is a plus

? Ability to multitask with attention to details

? Familiarity with financial analytics and time series econometrics is a plus

? Practical experience with semantic text analysis and deep learning is a plus

? Self-motivated and able to recognize long term needs and proactively address them

? Able to mentor junior data scientists through code reviews and best practices

? Strong leadership and project management skills

? Passion for transforming an organization

? Strong verbal and written communication skills


PhD or Master’s degree in an engineering/math/statistics/science discipline with 3+

respectively 5+ years of data science/machine learning experience and 1+ years of management



Competitive salary; stock options; health benefits; paid time off; life insurance.

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