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 audiences.

Model Deployment & Scaling: Implement and optimize machine learning models in production environments, ensuring they are scalable, efficient, and reliable

Mentorship & Leadership: Lead by example to build a culture of accountability and rigor to substantiate proven business impact with data, providing mentorship and guidance to other analysts on the team

Innovation: Keep current with technical and industry developments, tools, and technologies in the field of data science, and identify opportunities for continuous improvement and innovation within the organization. 

Physical Requirements & Attendance 

Acceptable level of hearing and vision to perform job duties

Adhere to company work hours, policies, procedures, and rules governing professional staff behavior

 Regular attendance required 

Full time

Equal Employment Opportunity

Academy is an Equal Opportunity Employer and does not discriminate with regard to employment opportunities or practices on the basis of race, religion, national origin, sex, age, disability, gender identity, sexual orientation, or any other category protected by law.​