Location: Santa Clara, CA, USA

Employment Type: Regular full time

Company:

Big Data Federation, Inc. is one of a new breed of asset managers on a quest to reinvent the investment process. We are unburdening humans of the manual job of making sense of endlessly growing volumes of data, and passing this responsibility onto machines. We believe our automated processes bring significant efficiencies in uncovering company fundamentals and driving fund outperformance.

We live by the motto “Nothing is random”.

Our home grown, 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. We are a team of technologists, mathematicians, economists, data scientists, and programmers backed up by one of the leading venture capital firms.

Job Profile:

Reporting to the Chief Data Scientist you will join an experienced and diverse team of software engineers and data scientists as a key contributor to our predictive analytics platform. You will work on 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.
We 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.

Experience:

  • 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
  • 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
  • Passion for transforming an organization
  • Strong verbal and written communication skills

Education:

PhD/Master’s degree in an engineering/math/statistics/science discipline with 2+ years of data science/machine learning experience

Compensation:

Competitive salary; stock options; health benefits; paid time off; short- and long-term disability life insurance;