- Company Name
- Otter.ai
- Job Title
- Data Scientist
- Job Description
-
Job Title: Data Scientist
Role Summary:
Data Scientist responsible for leveraging large datasets to drive product strategy, user engagement, and monetization within a SaaS environment. Works cross‑functionally with Product, Engineering, and Data Engineering to build predictive models, run experiments, and translate insights into actionable recommendations for senior stakeholders.
Expectations:
- Minimum 3 years experience as a Data Scientist in software or AI‑driven companies.
- Proven track record of building and deploying data models that influence product roadmaps and business outcomes.
- Ability to manage multiple concurrent projects in a fast‑paced, start‑up‑style setting.
Key Responsibilities:
- Partner with Product teams to translate business objectives into data problems and deliver insights that inform feature prioritization and monetization strategies.
- Design, develop, and productionise predictive models, statistical analyses, and visualisations using SQL, Python, and R.
- Analyse large usage and behavioural datasets to surface actionable patterns and recommend optimisations.
- Plan and execute A/B/tests, measure feature impact, and iterate on hypotheses.
- Collaborate with Data Engineering to maintain data pipelines, ensure data quality, and provide reliable analytics infrastructure.
- Communicate findings and recommendations effectively to executives, product managers, and technical teams.
- Stay abreast of industry trends, emerging technologies, and best practices in data science, ML, and AI, integrating relevant innovations into workflow.
Required Skills:
- Proficiency in SQL for querying large datasets.
- Expertise in Python and R for data manipulation, analysis, and visualisation.
- Strong background in statistical modelling, hypothesis testing, and machine‑learning techniques.
- Familiarity with B2B SaaS business models and metrics.
- Excellent communication skills, able to distil complex analyses into clear, actionable insights for non‑technical stakeholders.
- Collaborative mindset and proven ability to work across product, engineering, and data‑engineering teams.
- Strong problem‑solving orientation and resilience in dynamic, high‑growth environments.
Required Education & Certifications:
- Bachelor’s degree (or equivalent) in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
- Master’s degree or relevant certifications (e.g., Data Science, Machine Learning, or Big Data) preferred but not mandatory.
Mountain view, United states
Hybrid
07-01-2026