Principle Data Scientist/ Architect
Job Description
The Principal Data Scientist will design, develop and program methods, processes, and systems to consolidate and analyze structured / unstructured, diverse big data sources to generate actionable insights and solutions for client services and product enhancement.
They'll also build "products" for analysis. Interact with product and service teams to identify questions and issues for data analysis and experiments.
Develop and code software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
Identify meaningful insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to product, service, and business managers.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day.
We are an equal opportunity / affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.
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Required Skills & Experience
- 5+ years of Data Scientist experience
- 5+ years of Python experience
- 5+ years of Data Mining experience
- 5+ years of SQL query experience
- 5+ years of data cleansing experience
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching.
Employees in this role are also entitled to paid sick leave and / or other paid time off as provided by applicable law.
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