Data Scientist

Warren CAT•Oklahoma City, OK

3h•Onsite

About The Position

The Data Scientist is responsible for analyzing data and conducting important research to drive business decisions based on strategic goals for the organization. The Data Scientist acts as a trusted data visualization advisor to the stakeholder/end-user in order to drive business value. Work is somewhat complex in nature and performed under general supervision, requiring independent judgement.

Requirements

Bachelor's Degree in Data Science, Computer Science, Business Analytics or other business-relevant discipline from a four-year college or university; OR 4 additional years of relevant data and analytics or technical experience can be substituted in lieu of a degree in addition to the minimum years of work experience.
2 years of experience in data and analytics, technical, or business-relevant function; OR if Advanced degree in a STEM discipline, up to 2 years’ experience in data and analytics, technical, or business relevant function.
Entry level to intermediate knowledge of business intelligence platforms, data management platforms, or SQL-based languages (Tableau, NoSQL, TSQL, R, Python, or related).
Experience managing internal metrics, data, and business intelligence strategies.
Proficient in using analytical tools and instruments.
Ability to identify patterns in data.
Entry level to intermediate critical thinking and analytical skills for problem-solving.
Excellent presentation, communication and collaboration skills.
Entry level to intermediate level business acumen skills.

Responsibilities

Collaborate with cross-functional teams and key stakeholders to identify opportunities for data-driven solutions.
Conduct complex data analysis to identify and interpret trends, patterns, potential problems and opportunities to help inform and influence business decisions and drive value for the organization.
Recommend, visualize and communicate data driven solutions and insights to key stakeholders in a clear and compelling manner.
Identify data sources; collect structured and unstructured datasets and variables; build large, complex data sets to mine.
Manipulate raw data into aggregate tables for front-end usage.
Conduct data error analysis to improve models; clean and validate data for uniformity and accuracy.
Develop working knowledge of relevant data, information, and application architecture to influence decisions.
Understand key business priorities, marketing goals, customer segments, decision drivers and hypotheses, to create performance metrics.
Assist with developing, scaling and refining data modeling processes, analytical procedures, system workflows, data management etc.
Provide consultation regarding automation of data collection, data enhancement, and/or data storage processes.