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Staff Data Scientist

3 months ago

New York, United States Saks Full time

Who We Are:

Saks is a world-renowned luxury ecommerce destination. The companys unique approach combines a focus on the digital customer experience with a strong connection to a network of extraordinary stores that extends that seamless experience into the real world.

On its website and app, Saks offers an unparalleled selection of curated merchandise across fashion for women and men, beauty, jewelry, home decor and more. In addition to the shopping experience, customers come to Saks for inspiring editorial content, access to digital stylists, lifestyle experiences and other world-class services. The company is currently in the midst of a dramatic expansion, driven by significant enhancements to its platforms and offerings, with the goal of becoming the preeminent destination for luxury internationally.

Youre the kind of person who is:

  • Curious - You keep up with the industry trends and best practices and understand the when, why, and how to use them.
  • Not afraid - to roll up your sleeves and deal with any challenges presented to you including complex legacy systems.
  • Innovative - You can think outside the box. You learn from others but are not afraid to try something different.
  • Strong Believer - in automating the mundane and repetitive tasks and building reliable systems that only need minimal supervision.

Position Overview:

As a Staff Data Scientist ML/AI, you will play a pivotal role in designing, developing, and deploying ML/AI models to revolutionize our retail operations. You will work with cross-functional teams to create data-driven solutions that enhance product recommendations, optimize inventory management, and personalize customer interactions.

Role Responsibilities:

  • Model Development: Design, develop, and implement ML/AI models and algorithms to address specific retail challenges, such as personalized recommendations, automated content generation, and predictive analytics.
  • Data Engineering: Collaborate with data engineers to preprocess, clean, and structure data for model training and evaluation. Ensure data pipelines are optimized for efficiency and accuracy.
  • Machine Learning Operations (MLOps):
  • Deploy and maintain machine learning models in production environments (Astronomer, AWS, Snowpark). Implement MLOps practices to ensure scalability, robustness, and monitoring of deployed models.
  • Collaboration: Work closely with data scientists, software engineers, and business stakeholders to understand requirements and translate them into technical solutions.
  • Performance Optimization: Continuously evaluate and fine-tune models to improve performance and accuracy. Utilize feedback and metrics to enhance model effectiveness.
  • Documentation and Reporting: Maintain thorough documentation of model development processes and results. Communicate findings and insights to both technical and non-technical stakeholders.

Key Qualifications:

  • Seven or more years of deep learning experience
  • Education: Bachelors degree in Computer Science, Data Science, Engineering, or a related field. Advanced degree is a plus.
  • Technical Skills:
  • Proficiency in Python, including libraries such as TensorFlow, PyTorch, and scikit-learn.
  • Experience with Large language models llama, Claude, etc.
  • Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and their machine learning services.
  • Strong SQL knowledge for data manipulation and querying.
  • Worked with modern data warehouses like Snowflake or BigQuery
  • Used source control, Git and/or GitHub, proficiently
  • Familiarity with MLOps tools and practices for deploying and managing machine learning models.
  • Experience with data engineering practices and tools (e.g., ETL processes, data warehousing).
  • Worked in an agile team environment
  • Problem-Solving: Strong analytical and problem-solving skills with the ability to think creatively and strategically.
  • Communication: Excellent verbal and written communication skills, with the ability to present complex technical concepts to diverse audiences.

Your Life and Career at Saks:

  • Exposure to rewarding career advancement opportunities, from retail to supply chain, to digital or corporate.
  • A culture that promotes a healthy, fulfilling work/life balance
  • Benefits package for all eligible full-time employees (including medical, vision and dental).
  • An amazing employee discount

Thank you for your interest in Saks. We look forward to reviewing your application.

Saks provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Saks complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Saks welcomes all applicants for this position. Should you be individually selected to participate in an assessment or selection process, accommodations are available upon request in relation to the materials or processes to be used.

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