Data Scientist, Data Science

More than 30 years ago, ETRADE pioneered the online brokerage industry by executing the first-ever electronic individual investor trade. While the landscape of our industry has changed dramatically, our culture of innovation and drive to make online trading accessible to everyone continues to drive us forward. We believe in challenging the status quo, fostering an environment of curiosity and learning, and, above all, putting our customers first.

RESPONSIBILITIES

Leaders in Data Science can see different angles of a product or business opportunity, and you know how to connect the dots and interact with people in various roles and functions. You have substantial experience with analytical tools and techniques, and bring a solid skill-set in analyzing data and communicating recommendations. You will deepen your skill-set by working with analytical thought leaders across the company.

Data Scientists are changing the world one technological achievement after another.

Experimentation is at the core of what you do. In this role, you will work to effectively turn business questions into data analysis, and provide meaningful recommendations on strategy. This is a unique hybrid role that will focus on your knowledge of data infrastructure and your ability to drive insights.

As a Data Scientist, you will evaluate and improve E
TRADEs products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring analytical rigor and statistical methods to the challenges of measuring quality, improving customer products, and understanding the behavior of end-users, advertisers, and publishers.

Responsibilities

  • Work with complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of ETRADE data structure and metrics, advocating for changes where needed for both products development and strategy.
  • Interact cross-functionally with a wide variety of people and teams.
  • Make business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
  • Research and develop analysis, forecasting, and optimization methods to improve the quality of ETRADE's user facing products; example application areas include end-user behavioral modeling and customer segmentation.


REQUIREMENTS

Minimum qualifications:
  • BA/BS degree in quantitative discipline (e.g., statistics, operations research, economics, computer science, mathematics, physics, electrical engineering, inducstrial engineering).
  • At least 2 years of professional work experience in data analysis or related field. (e.g., as a statistician, data scientist, or economist)
  • Experience with statistical software (e.g., R, MATLAB, pandas) and data base languages (e.g., SQL).


Preferred qualifications:
  • Masters or PhD degree in quantitative discipline as listed in Minimum Qualifications.
  • Experience programming in Python.
  • 4 years of relevant work experience, including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
  • Applied experience with machine learning on large datasets.
  • Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.


We offer a competitive and comprehensive benefits package. Please visit https://www.etradecareers.com/why-work-at-etrade/employee-benefits/ to learn more about the opportunities.

E*TRADE Financial is an Equal Opportunity Employer who encourages diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, age, disability, citizenship, marital status, sexual orientation, gender identity, military or protected veteran status, or any other characteristic protected by applicable law.


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