Business Analyst, Hive Models
San Francisco
Hive – Product & Engineering /
Full-time /
About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!
Business Analyst, Hive Models
As a Business Analyst on the Hive Models team, you will work closely with our Machine Learning, Product, and Business Development teams to ensure successful client deployments of our products. A mix of product configuration, project management, and client success, this is a unique role that demands both technical competence as well as client management abilities. You will serve as the point person for major client engagements, taking on a wide range of responsibilities to ensure integration success.
Responsibilities
- Collaborate with engineering teams to ensure successful technical deployments
- Write scripts to analyze technical performance of production machine learning models
- Analyze customer submissions, data, and results to understand desired changes to the machine learning models
- Generate APIs for use by customers by ensuring accuracy of the technical configurations of the machine learning models
- Collaborate with the product team and other stakeholders to ensure customer needs are met, including resolving any technical issues that users run into while accessing our machine learning models
- Collaborate with the product and engineering teams as needed for other technical aspects of product deployment with customers
- Maintain awareness of industry best practices for data maintenance handling as it relates to your role
- Adhere to policies, guidelines and procedures pertaining to the protection of information assets
- Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
- You have a bachelor's or graduate degree in Computer Science or a related field, such as Engineering or Mathematics
- You have 1-3 years of work experience in a Product Management or Engineering role at a technology or technology consulting company
- You have working knowledge of functional programming languages such as Python or Node.JS
- You have experience in an interdisciplinary/cross-functional field. Added points for enterprise-technology, SaaS, client facing, or start-up experience
- You have distinctive problem-solving skills and impeccable business judgment
- You possess excellent written and verbal communication skills
Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $80,000 - $100,000. Actual compensation may vary depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
