Sr Data Scientist Enterprise

Come work at a place where we take pride in creating a workplace environment that values hard work, commitment, and growth.

Job Description:

Education 

• Bachelor's degree (BA, BS with strong coursework in a quantitative field, such as Engineering, in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, or a related field, or equivalent years of work experience

• Master’s degree preferred

Experience 

• 4+ Years in data analytics, business intelligence, or data engineering. Data Science Experience preferred

• 2 years in a senior analyst capacity, preferably within an enterprise or large-scale organization

• Experience with retail analytics + omnichannel will be a plus 

Skills 

• Ability to work well under pressure while consistently meeting time sensitive deadlines

• Ability to work well independently, as well as effectively contribute to a team environment

• Ability to prioritize workload, meet multiple deadlines simultaneously in a fast paced, frequently changing environment

• Strong interpersonal, written, and verbal communication skills, detail-oriented, with the ability to interact with all levels of end users and technical resources

• Proficiency in programming languages such as Python, R, or Scala

• Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn). Preference toward experience in a cloud enterprise environment, such as Google Cloud Platform (GCP) (BigQuery is a plus) / Azure / Amazon Web Services (AWS)

• Advanced knowledge of SQL and experience with relational and non-relational databases with a focus on transforming data to prepare for analysis and machine learning.  3+ years of experience in enterprise grade data visualization tools (e.g., Tableau, Power BI, Looker, MicroStrategy)

• Strong Microsoft Office program experience including Excel, Word, PowerPoint.  

Responsibilities: 

• Data Analysis & Modeling: Design and develop complex predictive and prescriptive models using advanced statistical and machine learning techniques. Utilizing data-science techniques, explore the data to uncover patterns and correlations, predict customer behavior, and preemptively identify potential problems.  Contribute to company A/B testing framework and recommend results

• Data Collection & Management: Lead the acquisition, integration, and cleaning of diverse and complex datasets from multiple sources to ensure data quality and reliability

• Data Product Ownership: Drive end-to-end data science products from ideation to production, including problem definition, data exploration, model development, and result validation, documentation, and monitoring. 

• Collaboration: Work closely with stakeholders across business units, including product, finance, marketing, operations, and IT, to understand business needs, define requirements, and align data science solutions with business objectives.

• Data Visualization & Communication: Create compelling visualizations and presentations that effectively communicate complex analysis, insights, and recommendations to both technical and non-technical audien