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Principal Data Scientist, Shopbop

Shopbop
New York, NY, US
Full-time

DESCRIPTION

Shopbop is seeking a Principal Data Scientist to build & lead a new team that will help us elevate how we inspire & delight our customers.

As a leader of this team, you will bring business and industry context to science & technology decisions that transform forecasting product demand & placement, ensuring we always have the right product in the right quantity at the right time and price.

You will Think Big to tackle intrinsically hard problems, acquiring expertise and building partnerships to accelerate shared success.

You will identify opportunities for Shopbop to experiment and innovate across demand prediction, product / outfit styling, and fit guidance and partner with Fashion experts, Buyers, Product Managers, and Engineers to implement solutions.

Your impact will create and grow a science competency throughout the company.

Key job responsibilities

As a hands-on leader of this team, you’ll need superior ability to quickly gather information and requirements from stakeholders, be responsible for defining key research questions, identifying relevant data, adopting or proposing innovative machine learning solutions conducting rigorous experiments, publishing results and working with the engineering team to deploy these solutions.

As a strategic leader, you will interact frequently with senior leadership, you will identify investment opportunities, develop long term strategies, and propose, prioritize and deliver on goals.

You’ll also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions.

You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

About the team

Shopbop’s mission is to be your destination for style inspiration and discovery. We operate at the forefront of fashion by offering a curated selection of ready-to-wear & accessories from established & emerging designers.

We are your daily source for what's new, offering best-in-class curations that inspire & delight every time you visit. We provide a shopping experience that is easy, innovative, and most of all, fun.

Simply put, we indulge your style obsession.

We are open to hiring candidates to work out of one of the following locations :

Madison, WI, USA Miami, FL, USA New York, NY, USA

BASIC QUALIFICATIONS

  • MS in Mathematics, Statistics, Machine Learning, or a related quantitative field
  • 7+ years industry experience building successful production software systems
  • Deep understanding and practical experience in several of the following areas : machine learning, statistics, recommendation systems, and forecasting
  • Excellent problem-solving skills with the ability to design algorithms, which may include data profiling, clustering, anomaly detection, and predictive modeling methodologies
  • Ability to combine skills to create new prototypes with the creativity and thoroughness to interrogate the most challenging questions

PREFERRED QUALIFICATIONS

  • Experience in Fashion, Seasonal products, e-commerce, or a related field
  • PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field
  • 10+ years of experience working in data science in aerospace, automotive or consumer electronics industries.
  • Significant peer reviewed scientific contributions in Data Science, Analytics, Statistics, Recommendation Systems or related field.
  • Extensive experience applying theoretical models in an applied environment
  • Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker.
  • Strong fundamentals in problem solving, algorithm design and complexity analysis
  • Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar)
  • Demonstrated industry leadership in the fields of Database and / or Data Warehousing, Data Sciences and Big Data processing.
  • 30+ days ago
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