Job Location: United States

*** This role is an initial 90 day contractor (C2C) opening, with a view to moving to a FT (Full Time) position afterwards (based on work and level of expertise) ***

Are you excited in joining a high growth, venture backed tech start-up, and become an integral part of an expert, nimble Data Science team, where vou will learn to thrive in a fast-paced environment with tons of cool and hard to solve problems?

They are seeking several Associate Data Scientists to join their rapidly growing team.

Our Client is a high growth startup in the Data Science as a Service (DSaaS) space for next generation brands and retail.

What does our Client provide?

1. Brands with a microscopic understanding of their customers based on individualized product preferences and geographical factors.
2. Intelligence driven data, which is used by all stakeholders across all functions, will inform, enhance, and optimize their decision-making
3. Resulting in an ever-optimizing flywheel that drives the acquisition and retention of high-value customers.

They seek a Junior Data Scientist (recent or current Graduates) who will initially focus on a Product Clustering Model. Ideally you will have a background building product recommendation engines.

• This role will report directly to the CTO based in New York.
• Culturally, you’ll be excited to join a high growth, venture backed tech retail/e-commerce start-up, and become an integral and critical part of a small, nimble, cross functional team.
• You will learn to thrive in a fast-paced environment with heaps of ambiguity and rapidly changing conditions.

Area of key focus:

• The Product Clustering model is an unsupervised learning model that groups customers
• based on the type of products they buy or do not buy.
• In other words, this model groups customers based on their buying behavior of specific products or categories.

The key areas of expertise (bolded) encompass 3 general areas:

1. Comfort with deconstructing different components of a product
2. Retail experience
3. Experience building recommenders
4. If you have experience that is adjacent or analogous that is also preferred

As well as other areas which include…

• Unsupervised Learning, Matrix Factorization, Neural Networks, Clustering Algorithm, and Latent feature modeling
• Proficiency in ML or Deep Learning with Python packages such as such as Sci-Kit Learn, Tensorflow or Keras
• Proven expertise in data cleaning and EDA in Python with packages such as Pandas, Numpy, plotly, seaborn, matplotlib
• Minimum of bachelor’s degree in quantitative field such as Statistics, Comp. Sci. Math, physics, EE, Mech. Eng,

Apply Here

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