Data Scientist

Pasadena, CA (Headquarters)Type: Full Time

We invite applications for a full-time data scientist position with training in the areas of statistical and machine learning to help the team with data analytics and product development in the field of behavioral economics. Looking for a new challenge or to kick-start your career with a fast-growing EdTech company? Join us on an exciting and challenging journey that is making a difference in education.

Responsibilities

We are looking for an outstanding candidate who is able to conceptualize, implement and tune predictive models, using unique behavioral data as input, to produce meaningful business insights, let it be hiring, retention predictions, or performance forecasting. Traits matching this role include an inquisitive mind showing an interest in behavioral and experimental economics, willingness to take on multiple roles, attention to details, hard-working attitude, and critical thinking skills when challenges arise.

  • Build, implement, and optimize predictive behavioral models by applying statistical, machine learning, and deep learning techniques.
  • Leverage strong math skills and statistical knowledge to advanced data mining and data analysis activities.
  • Decipher patterns within large quantities of data and reference key characteristics using visualization techniques.
  • Demonstrate strong programming skills in large-scale data analysis SQL, R, Python and Java.
  • Fully test algorithms and code to ensure the highest level of credibility, reliability, andmaintainability.
  • Interface with economists, development team, and project manager to formulate and suggestsolutions for analytics features and functionality.
  • Translate business questions into definable metrics and concrete actions. Ability to explainthe story the numbers are telling, test hypotheses with numerical data, and identify problemareas.
  • Complete written documentation and report results in the form of business reports, internaltechnology white papers, and statistical system documentation.
  • Hands-on, energetic, organized, meticulous attention to details, and a team player.

Qualifications

  • Advanced degree in a quantitative field such as computer science, statistics, data science, or informatics with a specialization in AI and machine learning is requiredExperience with data science toolkits and programming language, such as R, Octave, Python, Scala, Tensorflow.
  • Experience in Big Data such as MapReduce, PIG, or HIVE is a big plus.
  • Experience in data manipulation language such as SQL is a big plus.

Extra Credit

  • Scripting or programming experience.

References

  • Two references required.

Compensation

  • Compensation includes salary, stock options, bonus, and benefits commensurate with experience and qualifications.