Zip

Senior Data Scientist I

US
USD 100k - 140k
Machine Learning Python SQL Deep Learning
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Description
  • Senior Data Scientist with expertise in developing and deploying advanced machine learning models, with strong proficiency in Python, PySpark, and SQL, and a solid background in statistics and finance/fintech
  • Thrives on creative and critical thinking to design, validate, and deploy impactful models, collaborating across teams and adapting to new technologies to drive business-wide decision-making and enhance customer experiences
  • Remote-first opportunity for US-based employees with the option to work in person out of our Manhattan office 

Start your adventure with Zip 

As a Senior Data Scientist, you will leverage your creative and critical thinking skills to develop best-in-class models that meaningfully impact the Zip team. These models will support risk management, customer experience, marketing, and beyond.

As part of the Data Science squad, you’ll be given free reign to experiment and think critically - and creatively - to develop best-in-class Machine Learning models that support business-wide decision-making. We’ll look to you to understand the business problem, design and optimize the machine learning solution, and deploy it in a way that adds real value to your customers' and fellow Zipsters' lives.

Interesting problems you’ll get to solve

  • Develop, validate, and deploy ML models to solve complex problems and communicate ideas to internal stakeholders
  • Extract and explore data, validate data integrity, perform ad hoc analysis, evaluate new data sources to improve models
  • Maintain robust documentation of approach and techniques used, including objectives, assumptions, performance, weaknesses, and limitations
  • Be ready to adapt to new tools/libraries/technologies/platforms
  • Actively partner with engineers to validate & deploy scalable solutions
  • Collaborate to gather insight from partners across the organization
  • Further develop expertise in data science and engineering through self-study, project exposure, and guidance of senior team members

What you’ll bring to the team 

  • Bachelor's Degree in a quantitative field (e.g., computer science, data science, engineering, economics, mathematics, etc.). Masters/Advanced degree preferred.
  • 4-6 years of Data Science experience 
  • 2+ years of Finance/Fintech industry experience required / Prior experience in building credit underwriting models (consumer) preferred.
  • Demonstrated knowledge in Statistics and Machine Learning Modeling.
  • Experience building and deploying models in production is preferred 
  • Proficiency in Deep Learning methods is a big plus
  • Proficient with Python
  • Proficient with PySpark and SQL
  • Self-driven with an aptitude for independent research & problem-solving
  • Being able to multitask in a fast-paced environment is essential

What you’ll get in return

Zip is a place where you’ll get out what you put in. The newness of our sector means we need to move at pace and embrace change, and our promise to you when you join the team is that you’ll feel empowered and trusted to make big things happen quickly. 

We want you to feel welcome and as though you have the support to be yourself, and care for yourself at work. Because it’s important to us that you make the most of the opportunities you’ll get to grow your skills and your career, and be surrounded by smart, friendly people and leaders that have your back.

We think these are just some of the best things about being a Zipster. We will also offer you:

  • Flexible working culture
  • Incentive programs
  • 20 days PTO every year
  • Generous paid parental leave
  • Leading family support policies
  • 100% employer covered insurance
  • Beautiful Union Square office with a casual dress code
  • Learning and wellness subscription stipend
  • Company-sponsored 401k match

The Pay Range for this position: $100,000 - $140,000 based on the industry benchmark for position, function, level and Zip's compensation strategies. However, actual base salary will depend on varying circumstances and individualized factors, such as job-related knowledge, skills, experience, and other objective business considerations. 

Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards, in addition to a full range of medical, financial, and/or other benefits. 

Be a part of a team that reflects the diversity of our customers

We pride ourselves on being a workplace that provides equal opportunities to people of all ages, cultural backgrounds, sexual orientations, gender identities, abilities, veteran status, and everything else that makes you unique.

Equally, we’re committed to ensuring our recruitment processes are accessible and inclusive. Please let us know If there are any adjustments that need to be made to ensure you have a fair and equitable experience.

And finally…get to know us

Zip Co Limited (ASX: ZIP) is a digital financial services company, offering innovative, people-centred products.

Operating in two core markets - Australia and New Zealand (ANZ) and the US, Zip offers access to point-of-sale credit and digital payment services, connecting millions of customers with its global network of tens of thousands of merchants.

We’re proud to be a values-led business and our values - Customer First, Own it, Stronger Together and Change the Game - guide us in everything we do.

I acknowledge by clicking "Submit Application", that the information provided is true and correct. I also understand that any willful dishonesty may render for refusal of this application or immediate termination of employment. By providing your information, you acknowledge that you have read our Zip Applicant and Candidate Privacy Notice and authorize Zip to process your data subject to those terms

Before you apply, give Zip a try   -> rebrand.ly/check-zip-out

We are a proud 2024 Circle Back initiative employer and will respond to every applicant.

Zip
Zip
Finance Financial Services FinTech Payments

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