Platform Engineer - Data Science and Machine Learning at Thrasio (Remote)
Sorry, this job was removed at 8:38 a.m. (EST) on Tuesday, May 3, 2022
Hop on the Rocketship
Thrasio is a next-generation consumer goods company reimagining how the world’s most-loved products become accessible to everyone. We use a deep understanding of rankings, ratings, and reviews to identify and acquire quality brands and use world-class expertise and data science to make their products better or create new ones to meet changing customer demand.
We’ve got huge goals, and every Thrasher plays an integral part in getting us to the stratosphere. That’s why we only bring on people who think positively. Who look out for the team. Who tell their egos to take a hike while they get the job done right.
From the moment you hop on our rocketship, we give you the freedom you need to take big swings and push what’s possible to get us there. And if you fail, it’s cool—we know you’ll grow spectacularly. What matters is that you’re helping impact millions of people around the world who use our products everyday.
Because with every new spatula, pillow, or marker brand we acquire, with every coffee roaster or body wash we develop, our goal is to provide people everywhere with what they need to make the most of every moment - ensuring that what gets delivered to their door delivers.
With the experience of evaluating more than 6,000 Amazon companies, acquiring over 130 top-rated brands, and managing the scale of 22,000 products, Thrasio is the largest acquirer of Amazon FBA brands. Since our founding in 2018, the team has grown to more than 1,000 people globally--most of that growth has occurred during the COVID-19 pandemic. Hiring people who share a passion for their craft in the eCommerce space is the reason we’re projected to grow more than 10x in the next few years. This growth is supported by investors whose portfolios include Facebook, Google, Jet.com, StitchFix, and Lululemon. We do our best work when we’re surrounded by people who are insatiably curious, agile, and who thrive in collaborative, check-your-ego-at-the door working environments. Sound like you? We’d love to chat.
In this role, you will be the center of enabling a platform for data-driven decision making and applied research for the company as we use the latest ML/DL and data science techniques to continuously optimize every aspect of the business, including inventory management, forecasting, acquisition target recommendation, keyword optimization, and a whole new category of decision management for day to day operations. You will be a Platform Engineer on the Data Science & Machine Learning team.
What you'll do:
- Designing, building and owning the Data Science & Machine Learning Platform which include Data Science and Machine Learning infrastructure, applications, libraries, model training pipelines and CI/CD pipelines for our algorithmic engines to run at scale
- Optimizing compute resources for data science and machine learning models, services and pipelines such as runtime and memory usage
- Implement and improve logging, monitoring and alerting to improve data quality and management
- Interfacing with data scientists, data engineers, software engineers, and product managers to build services, libraries, and infrastructure
- Requesting cross functional feedback by writing technical documents to communicate design and architecture decisions, implementation strategies, risks and timelines
- Being proactive and taking strategic initiative by being a team player
- Understanding and optimizing the Data Science life-cycle from conception to prototyping, testing, deploying, and aligning projects to overall business value
- Deliver presentations to high level business stakeholders that tell cohesive, logical stories using data - while this is primarily a technical role, we value the communication of ideas and want to expose engineers to the company at large
- Providing technical and microservices platform support where needed
What you bring to the party:
- 2+ years of experience in engineering or full-stack data science
- Highly proficient in Python and SQLProficient with Linux operating system and Unix
- Ability to communicate technical concepts verbally and in writing
- Experience with CI/CD, observability, automated testing, monitoring and alerting
- Intuitive sense of how quantitative and technical work aligns closely with business priorities and business value
- Some understanding of Data Science and Machine Learning techniques Flexibility and adaptability with eagerness to learn quickly
- Be really excited to build something new for a business disrupting e-commerce
- Bachelor's Degree in Engineering or Computer Science or equivalent experience
Nice to have, but not required:
- Masters’ Degree in Engineering and/or Computer Science and 5+ years of experience in engineering or full-stack data science
- Engineering for a company specializing in e-commerce or finance & acquisitions
- Familiarity with Amazon AWS, Databricks, Snowflake, Plotly, and Kubernetes
Research shows that while men apply to jobs when they meet an average of 60% of the criteria, women and other marginalized folx tend only to apply if they meet 100% of the qualifications.
At Thrasio, we need people who think rigorously and aren’t afraid to challenge assumptions, so we’re looking for diverse perspectives, as long as you meet the minimum criteria. You’re encouraged to apply even if your experience doesn’t precisely match the job description. Join us!
THRASIO IS PROUD TO BE AN EQUAL OPPORTUNITY EMPLOYER AND CONSIDERS ALL QUALIFIED APPLICANTS FOR EMPLOYMENT WITHOUT REGARD TO RACE, COLOR, RELIGION, SEX, GENDER, SEXUAL ORIENTATION, GENDER IDENTITY, ANCESTRY, AGE, OR NATIONAL ORIGIN. FURTHER, QUALIFIED APPLICANTS WILL NOT BE DISCRIMINATED AGAINST ON THE BASIS OF DISABILITY, PROTECTED CLASSES, OR PROTECTED VETERAN STATUS. THRASIO PARTICIPATES IN E-VERIFY.
Thrasio does not accept agency resumes. Please do not forward resumes to our jobs alias, Thrasio employees or any other organization location. Thrasio is not responsible for any fees related to unsolicited resumes.
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