Data Scientist (New York)
Stott and May, New York, NY, United States
Data Scientist / Data Engineer (Ecommerce) Contract Opportunity
Work:
We’re supporting an ecommerce client looking for a hybrid
Data Scientist / Data Engineer
contractor to help scale data products and drive insights across customer, product, and digital performance data.
Responsibilities:
Build and maintain data pipelines supporting analytics and machine learning use cases
Develop models and analyses around customer behavior, recommendations, forecasting, and conversion optimization
Work with large-scale ecommerce data (clickstream, transactions, inventory, marketing)
Design and optimize datasets for reporting, experimentation, and predictive modeling
Partner with analytics, product, and engineering teams to productionize solutions
Support data quality, performance tuning, and scalable data architecture
Requirements:
Strong Python and SQL skills
Experience in both data engineering and data science / ML workflows
Background building pipelines with tools like Airflow, Spark, dbt, or similar
Experience with cloud platforms such as AWS, GCP, or Azure
Exposure to recommendation systems, forecasting, customer analytics, or experimentation (A/B testing) preferred
Ecommerce, retail, or marketplace data experience strongly preferred
Details:
Fully remote
40 hours/week (full-time
contract )
Initial 6-month
contract
with likely extension
W2 or personal LLC only ( no C2C )
Rates competitive and dependent on experience (target $80–$110/hr)
Work:
We’re supporting an ecommerce client looking for a hybrid
Data Scientist / Data Engineer
contractor to help scale data products and drive insights across customer, product, and digital performance data.
Responsibilities:
Build and maintain data pipelines supporting analytics and machine learning use cases
Develop models and analyses around customer behavior, recommendations, forecasting, and conversion optimization
Work with large-scale ecommerce data (clickstream, transactions, inventory, marketing)
Design and optimize datasets for reporting, experimentation, and predictive modeling
Partner with analytics, product, and engineering teams to productionize solutions
Support data quality, performance tuning, and scalable data architecture
Requirements:
Strong Python and SQL skills
Experience in both data engineering and data science / ML workflows
Background building pipelines with tools like Airflow, Spark, dbt, or similar
Experience with cloud platforms such as AWS, GCP, or Azure
Exposure to recommendation systems, forecasting, customer analytics, or experimentation (A/B testing) preferred
Ecommerce, retail, or marketplace data experience strongly preferred
Details:
Fully remote
40 hours/week (full-time
contract )
Initial 6-month
contract
with likely extension
W2 or personal LLC only ( no C2C )
Rates competitive and dependent on experience (target $80–$110/hr)