Product Manager - Machine Learning
Greater NYC Area
At HyperScience, we use modern machine learning to turn documents into machine-readable data. Our customers receive a wide variety of documents, like life insurance applications, paystubs, utility bills, insurance claims, that must be processed quickly and accurately to better serve the people at these organizations, and their customers. Amazingly, this is all done manually today. We’re on a mission to change that!
Our product is already delivering value to large, blue-chip organizations in financial services and insurance, and we see a massive opportunity to expand to more industries and automate more business processes. We are looking for people who are excited to help us build upon this foundation and vision.
Founded in 2014 by Peter Brodsky, Vladimir Tzankov, and Krasimir Marinov, Hyperscience has raised over $48 million from SV Angel, The Stripes Group, Firstmark, Battery Ventures, and Felicis Ventures.
As we continue to build machine learning for office work, we're looking to grow our Product Management team to face new challenges in the space. You will be working directly with our world-class machine learning engineers in NYC and Sofia, to improve and build upon our products. While we're currently working on data extraction, our ambitions and goals are much larger and the Machine Learning team will play a key role in achieving the next wave of success for HyperScience. We see this role growing as we introduce new products and functionality to the market over time.
- Within your first month, you will work with our Machine Learning team to understand our model training and evaluation processes and their accompanying analytical frameworks and tools. You will work with team leads on features to push out the accuracy frontier on your current models
- After 60 days, you will be able to answer any question about our ML efforts and you'll know the connections between your team's models and the end to end workflow within our product. You will be the go-to person across all functional areas for all things related to ML performance, accuracy metrics, and future product feature requests
- After an entire quarter and beyond, you will fully own your team's roadmap taking into account an expanding product footprint requiring new ML capabilities. You will be responsible for building and maintaining success metrics as well as reporting them to the broader product and engineering teams
- Excellent analytical and diagnostic skills
- 3+ years in a product management role at a tech company
- Strong communication (written and verbal) skills working with remote teams
- Strong product sense and deep understanding of what makes products effective
- A high degree of comfort with ambiguity - you’re able to quickly develop hypotheses with limited information
- Self-motivated and willing to handle competing priorities in a fast-paced environment
- Previous experience in a highly analytical or quantitative role preferred
- Familiarity with machine learning methods and technologies
- Experience in enterprise software development
Benefits & Perks
- Top notch healthcare for you and your family
- 30 days of paid leave annually to help nurture work-life symbiosis
- A 100% 401(k) match for up to 6% of your annual salary
- Stock Options
- Paid gym membership
- Pre-tax transportation and commuter benefits
- 6 month parental leave (or double salary to pay for your partner's unpaid leave)
- Free travel for any person accompanying a breastfeeding mother and her baby on a business trip
- A child care and education stipend up to $3,000 per month, per child, under the age of 21 for a maximum of $6,000 per month total
- Daily catered lunch, snacks, and drinks
- Budget to attend conferences, train, and further your education
- Relocation assistance
We are an equal opportunity employer. We welcome people of different backgrounds, experiences, abilities and perspectives. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.
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