Lead Data Scientist

About the role

Senior Data Scientist

Remote, with occasional travel to HQ in Oklahoma

FTE

$120-140K with excellent bonus scheme

Financial Services sector

US CITIZENS ONLY

Job Description:

Work with large, complex data sets using to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed to complete end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Engineer analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed in systems, products and processes.

Research and engineer analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence and optimization methods to improve the quality of products; example application areas include customer segmentation modeling and end-user behavioral modeling/prediction.

Technical Skills and Requirements:

Expert in multiple statistical software (e.g., R, Python, Julia, MATLAB, pandas) and associated data science libraries (scikit-learn).

Expert in database languages (e.g., SQL).

Experience creating meaningful data visualizations and/or interactive dashboards that communicate findings and business impacts using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js.

Applied experience with machine learning on large datasets using Big Data tools such as Apache’s Hadoop or Spark

Expert in deep learning techniques and neural networks using languages such as as TensorFlow

Expert in multiple major programming language (C/C++. C#, Java, Python, etc.) or optimization modeling languages (AMPL, GAMS, AIMMS, OPL, etc.)

Experience with data science methods related to data architecture, data cleaning, data and feature engineering, and predictive analytics.

Strong background in modeling large scale discrete, nonlinear or stochastic mathematical optimization models and engineering efficient optimization algorithms.

Familiarity with natural language processing, machine learning, statistical modeling, predictive modeling, and hypothesis testing.

Familiarity working with both structured and unstructured data, including textual data.

Ability to work in a fast-paced environment.

Exceptionally strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.

Education:

Master's degree in related field required.