Data Scientist [Multiple Positions Available]

Duties: Develop and apply statistical and mathematical models to analyze complex data trends and patterns using programming tools and data analysis software languages.

Generate analytical insights and develop statistical solutions that streamline business processes, uncover new opportunities, and bolster strategic decision-making.

Conduct research on market trends and perform analysis of internal data.

Utilize findings to craft actionable insights, guiding the strategic direction of the organization and identifying potential areas for product innovation and growth.

Collaborate with cross-functional teams across product, business, and technology departments to implement data-driven strategies, in order to create and refine analytical models and algorithms.

Document and communicate complex technical and analytical results tailored for a non- technical audience.

Design and develop the analytical framework and algorithms for the automated application booking process for car dealers.

Process monthly reporting of KPI, highlighting any anomalies in trend for senior leadership.

This position requires up to 10% domestic and international travel.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Business Analytics, Information Management, Data Science, Statistics, Mathematics or related field of study plus 3 years (36 months) of experience in the job offered or as Data Scientist, Package Specialist, Data Analyst or related occupation.

The employer will alternatively accept a Bachelor's degree in Business Analytics, Information Management, Data Science, Statistics, Mathematics or related field of study plus 5 years (60 months) of experience in the job offered or as Data Scientist, Package Specialist, Data Analyst or related occupation.

Skills Required: This position requires three (3) years of experience with the following: data processing and ETL (Extract, Transform, Load) procedures to extract data from multiple source systems for modelling and dashboarding; using Machine learning (ML) scripting languages, including Python and R to develop predictive models; utilizing ML algorithms such as logistic regressions, KNN, random forest, and Gradient boosting for classification problems; using private and public big data platforms, including AWS for scalable computation; using statistical concepts for data analysis, including normal distribution, Bernoulli distribution, Bayesian inference, and sampling data to derive inference; developing analytical solutions for business operations utilizing data analysis with statistical software such as R or Alteryx; presenting business insights and economic research results to a non-technical audience, by performing statistical analysis.

This position requires two (2) years of experience with the following: using database systems such as Teradata, Oracle, or Snowflake, for establishing connections, designing, maintaining, and fetching data from schemas and tables; using SQL for database quer...