When you choose DataHouse, you become part of an entrepreneurial culture that is passionate about making customers succeed through innovative technologies. Celebrating 40 years of innovation, we continue to nurture the unique dynamics of our culture that allows for creative solution discovery, innovative explorations and professional growth.
Successful candidates will also have the ability work with clients to identify areas where data and analytics can address critical issues, and then deliver value by developing and deploying analytical methodologies and solutions. The Data Scientist will also work to identify new analytics opportunities and contribute in the drafting and pitching of analytics projects to prospective clients.
· Understand and document our clients’ business needs and existing data flows. Identify where analytical processes can add value to the client and prescribe an appropriate solution to fit their context.
· Perform, summarize, and translate insights gained from data analyses (including data profiling and exploration, hypothesis testing, and statistical modeling) using either R or Python.
· Scope and build analytics environments using open-source technologies as well as off the shelf packaged solutions.
· Assist in the drafting and pitching of proposals for prospective clients.
· Work with project management to help create and execute analytics work plans.
· Work with clients to identify areas where analytics can deliver value, develop relevant analytics use cases, identify, acquire, clean, and organize needed data sets.
· Deliver technical training to clients on how to run and maintain delivered analytics packages.
· Bachelor’s or Master’s degree in Computer Science, Information Systems, Statistics, Mathematics, or related fields
· A strong understanding of statistical modeling and machine learning techniques and model evaluation metrics. This includes supervised and unsupervised machine learning, regression analysis, and forecasting.
· Proficiency with R (RStudio), Spark ML, and/or Python (pandas, numpy, scipy, etc.) coding languages and libraries
· Proficiency with SQL and/or NoSQL
· Proficiency with static and/or interactive data visualization tools and libraries like Tableau, Shiny, ggplot2, D3, and Vega
· Strong written and verbal skills with the ability to draft and pitch proposals to clients
· Ability to translate scientific insights into product decisions, processes, and data driven management
· Experience working with distributed file systems
· Proficiency with GIS software
· Experience with using APIs to source data
· Proficiency in a core programming language (Python, C/C++, Java, Ruby, etc).