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Responsive (formerly RFPIO) is the global leader in strategic response management software, transforming how organizations share and exchange critical information. The AI-powered Responsive Platform is purpose-built to manage responses at scale, empowering companies across the world to accelerate growth, mitigate risk and improve employee experiences. Nearly 2,000 customers have standardized on Responsive to respond to RFPs, RFIs, DDQs, ESGs, security questionnaires, ad hoc information requests and more. Responsive is headquartered in Portland, OR, with additional offices in Kansas City, MO and Coimbatore, India. Learn more at responsive.io.
About the Role
Responsive is currently in search of a dynamic Data Scientist equipped with analytical, statistical, and programming prowess to harness significant volumes of data and craft tailored solutions that precisely align with organizational needs.
Your primary responsibility will involve delving into extensive unstructured datasets to identify trends that can drive business growth and yield substantial revenues. This role demands exceptional analytical skills coupled with a solid foundation in analysis, mathematics, and statistics. Critical thinking and problem-solving abilities are paramount for interpreting data effectively. Moreover, familiarity with AI tools is essential to automate processes and engineer intelligent solutions that empower the organization to thrive in a competitive market landscape.
Your overarching objective will be to facilitate trend analysis, enabling informed decision-making across the business.
Essential Functions
- Conducting large-scale data gathering, cleansing, and organization from diverse sources.
- Developing and applying statistical models and algorithms for data analysis and predictive purposes.
- Employing data visualization techniques as needed to present findings and insights clearly to stakeholders.
- Sound understanding and good experience in Generative AI and LLM.
- Managing both structured and unstructured data during preprocessing stages.
- Delivering concise and compelling presentations of results.
- Proposing innovative approaches and techniques to address corporate challenges.
- Designing and deploying machine learning models for various applications, including fraud detection, consumer segmentation, and predictive maintenance.
- Staying updated on the latest advancements in data science and embracing new methodologies as required in your role.
Education
Experience
Knowledge, Ability & Skills
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