Data Scientist

David Yurman•New York, NY

7d•$140,000 - $155,000•Hybrid

About The Position

The Data Management, Engineering and Analytics team at David Yurman (DY) is responsible to design & implement state of the art data management & analytics solutions. We are looking for a Data Scientist to design and build data analytics solutions to support DY’s strategic business goals. The Data Scientist performs data analysis to support David Yurman (DY) business operations. The team is in a formation state, and this is an exciting time to join and grow with an organization which is rapidly growing for the past few years.

Requirements

4-5+ years of professional experience as a data scientist.
5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).
3-5 years’ experience with quantitative analysis, experimentation, regression, data mining.
3-5 years’ experience working with large and complex data sets to solve a wide array of challenging problems using analytical and statistical approach.
Experience with retail analytics using statistical modeling a plus.
Self-starter and positive performer who can flex when priorities change, collaborate with cross functional partners, contribute to the team’s overall success.
Strategic thinking, excellent writing, and professional editing skills.
Experience with reporting / visualization tools Tableau, Sigma etc.
Bachelor’s degree in data science, computer science, or another related field.

Nice To Haves

Python/ R, Snowflake certifications desirable

Responsibilities

Query and acquire the data required to perform business analysis and identify trends in large data sets that answer business critical questions.
Drive data driven decision making by interpreting the data and providing adequate business insights.
Develop data mining processes, and machine learning models to support data analytics provided.
Develop, maintain and enhance AI / ML models to support business teams such as CRM, Marketing, Demand Planning, Business Strategy etc.
Leverages ML / other relevant statistical techniques to identify business performance improvement opportunities to drive favorable outcome.
Research existing and emerging data science principles, theories, and techniques to best inform business decisions.
Ability to develop Work on multiple data integration projects simultaneously.
Develop appropriate test scripts and test the models and analytics.
Keep track of the technology advancements in the areas of ML & AI and bring the industry best practice to the team.