Data Scientist/Sr. Data Scientist Fort Worth, TX

ESRhealthcare•Fort Worth, TX

15d•Onsite

About The Position

openings for a Data Scientist/Sr. Data Scientist to perform the following duties: Gather data from various analytical databases and sources, and implement advanced statistical methodologies to optimize operations; Obtain, manipulate, clean, and analyze structured and unstructured data from diverse sources; Conduct exploratory analyses including hypothesis testing, statistical inference and statistical analysis (predictive and/or prescriptive); Partner with business and technical stakeholders to translate challenging retail business problems into state-of-the-art data science solutions; Work with other teams across the organization to integrate and centralize customer data for analytics purposes to increase customer knowledge across the organization, including but not limited to third party data, digital behavior, operational metrics, etc.; Deploy models as proofs-of-concept or fully productionized implementations; Develop, analyze, and evaluate customer centric metrics that incorporate customer attributes and behaviors holistically and allow the company to better understand customer value; Collaborate cross-functionally across workgroups to add customer insights leading to better decisions; Select appropriate analytical tools and write analytics-based code and queries to generate outputs supporting strategy and decision-making; Identify and assess opportunities to leverage new technologies and collaborate with external vendors to enhance customer understanding. Work Schedule: 40 hours per week/8 a.m.-5 p.m./M-F. Job Location: Fort Worth, TX

Requirements

2 years of experience as Analyst or any occupation in which the required experience was gained, and demonstrated experience in: Business analysis
Reporting and data analysis for sales or service teams
Advanced MS Excel and PowerPivot skills to model large amounts of data
Data visualization and reporting on Tableau or Microsoft Power BI
Statistics and forecast modeling
Statistical and descriptive concepts and methodologies
SQL or related data querying and manipulating tool
Strong knowledge of quantitative analysis using Python
Pulling and analyzing data from complex and big data sources
Strong economic and market analysis skills
Strong analytical skills with work experience in dynamic environment
Demonstrated ability to solve and to lead others in solving complex analytical problems
Competitive analysis
Database management systems, data structuring, and data architecture
Machine learning methods including correlation, clustering, segmentation, and regression
Machine learning algorithms including XGboost, KNN Neighbors, and Random Forest
Data extraction, cleaning, and analysis
Cloud Computing or Distributed Computing
Azure Databricks or Spark

Responsibilities

Gather data from various analytical databases and sources, and implement advanced statistical methodologies to optimize operations
Obtain, manipulate, clean, and analyze structured and unstructured data from diverse sources
Conduct exploratory analyses including hypothesis testing, statistical inference and statistical analysis (predictive and/or prescriptive)
Partner with business and technical stakeholders to translate challenging retail business problems into state-of-the-art data science solutions
Work with other teams across the organization to integrate and centralize customer data for analytics purposes to increase customer knowledge across the organization, including but not limited to third party data, digital behavior, operational metrics, etc.
Deploy models as proofs-of-concept or fully productionized implementations
Develop, analyze, and evaluate customer centric metrics that incorporate customer attributes and behaviors holistically and allow the company to better understand customer value
Collaborate cross-functionally across workgroups to add customer insights leading to better decisions
Select appropriate analytical tools and write analytics-based code and queries to generate outputs supporting strategy and decision-making
Identify and assess opportunities to leverage new technologies and collaborate with external vendors to enhance customer understanding