About Appriss Retail

Appriss Retail provides real-time decisions and active risk monitoring to enable our customers to maximize profitability while managing risk.  Our solutions are continually adapting to changing market conditions. 

We bring 20+ years of retail data science expertise and experience.  We serve a global base of leading commerce partners, representing 1/3 of all US omnichannel retail sales activity across 150,000 retail locations across specialty, apparel, department store, hard goods, big box, grocery, pharmacy, and hospitality businesses in 45 countries on six continents.

The company provides compelling, relevant, and profitable collective intelligence to operations, finance, marketing, and loss prevention. Appriss Retail’s performance-improvement solutions yield measurable results with significant return on investment.

About the role

The Data Scientist will play a hands-on role in building, maintaining, and enhancing our production-level data infrastructure. This position is ideal for someone with strong Python and SQL skills who can contribute directly to our code base—especially for data engineering pipelines and MLOps-related functionality. You’ll be expected to write clean, maintainable, and production-ready code, with a focus on scaling our data workflows and supporting deployment in cloud environments. While this role may involve statistical and machine learning work, the primary emphasis is on engineering-quality coding, pipeline development, and operationalizing models and data products. A successful candidate combines strong coding skills with deep curiosity about the data they are working with and the surrounding business context. 

This temporary role is expected to last about six months, with the possibility of extension based on business needs.

What you'll do

• Write, maintain, and optimize production-level Python and SQL code for data pipelines, MLOps workflows, and related systems. 

• Analyze structured and unstructured datasets to identify trends, patterns, and opportunities for improvement. 

• Design, implement, and maintain automated data ingestion, transformation, and validation pipelines. 

• Contribute to the design, testing, and deployment of predictive and prescriptive models. 

• Support deployment of pipelines and ML models, including standing up and managing relevant cloud infrastructure. 

• Collaborate with engineering, product, and business teams to translate requirements into scalable, code-driven solutions. 

• Apply rigorous statistical and software engineering best practices to ensure accuracy, reproducibility, and reliability. 

• Continuously evaluate and integrate tools, frameworks, and methods that improve efficiency, scalability, and maintainability. 

• Communicate results and recommendations clearly to both technical and non-technical audiences. 

• Adhere to data governance, security, and privacy standards. 

Qualifications

• Master’s Degree in Computer Science, Data Science, Statistics, Mathematics, or related field (Bachelor’s degree with significant relevant experience considered). 

• Proven track record of writing production-ready Python and SQL code. 

• Familiarity with common data and ML libraries (e.g., dbt, pandas, NumPy, scikit-learn). 

• Strong SQL skills and experience with large, complex datasets. 

• Experience in end-to-end data project delivery—from code development to deployment. 

• Familiarity with version control (Git) and collaborative coding workflows. 

• Strong understanding of software engineering principles in a data science context. 

• Experience with statistical modeling, machine learning, and A/B testing. 

• Ability to communicate technical concepts clearly and effectively. 

• Commitment to producing high-quality, maintainable, and scalable code. 

Preferred Qualifications

• Experience with cloud platforms (e.g., Azure, AWS, GCP) and deploying data pipelines in the cloud. 

• Familiarity with MPP platforms (e.g., Snowflake, Databricks, Greenplum). 

• Experience with MLOps tools, CI/CD workflows, and infrastructure as code. 

• History of standing up or managing cloud infrastructure to support data pipelines and ML deployment. 

Benefits

At Appriss Retail, we offer a competitive and comprehensive benefits package designed to support your well-being at work and beyond. Benefits begin on your first day and include multiple medical plan options, dental and vision coverage, health savings and flexible spending accounts, paid parental leave, and supplemental coverage for life’s unexpected moments. We offer generous paid time off, a 401(k) with immediate vesting and company match, short- and long-term disability, and free access to health and wellbeing resources such as Calm and Rocket Lawyer. You’ll also have access to learning and development opportunities to help you grow your career. Our benefits support your well-being so you can perform your best in every part of life.