---
title: 'Data Scientist ll at wyzecam.com'
canonical: 'https://feeny.ai/job/data-scientist-ll-wyzecam-com-kirkland-pdmb7s6wvxnz'
type: 'job'
last_seen: '2026-10-16'
---

# Data Scientist ll at wyzecam.com

- **Company:** wyzecam.com
- **Location:** Kirkland, WA
- **Compensation:** $121k–$150k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-15
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.gem.com/wyzecam-com/am9icG9zdDqJ-QKmvXmrzc8caIoH5Q7m

## Job description

We're looking for a Data Scientist to help improve the quality, organization, and usability of the data that powers our AI/ML products. This isn't a reporting or dashboarding role — you'll be training, updating, and running models directly against large-scale datasets, diagnosing systemic quality issues, and building the frameworks that determine what data is fit for training. You'll work at the intersection of applied machine learning, data quality engineering, and analytical tooling.

## What You'll Do

- Assess and structure training data: Evaluate large-scale datasets for quality, apply structured labeling frameworks, and diagnose systemic gaps or inconsistencies that affect model performance
- Train, update, and apply models against existing data: Train or fine-tune models, apply scoring/classification tools against datasets to auto-tier or flag quality at scale, and iterate on models as new data or requirements emerge
- Surface insights: Explore labeling and usage patterns to find where data quality is strong or weak, and turn findings into clear, defensible recommendations
- Support data pipeline integration: Partner with engineers to ensure clean, well-labeled data flows smoothly into downstream systems and model training workflows
- Test and validate: Validate model outputs and quality-scoring results against ground truth before they're used downstream, and monitor for drift or regressions as data and models evolve
- Contribute to tooling improvements: Provide input on internal tools used for data labeling and review, helping shape what they need to track, automate, or support
- Build quality frameworks: Define metrics and benchmarks that answer “how good is our data?” and track them over time, with a direct eye toward how data quality impacts model performance

## What We're Looking For

- Master's degree in Data Science, Statistics, Computer Science, or a related quantitative field
- 1–4 years of experience in data science, machine learning, or a related quantitative field
- Solid understanding of machine learning fundamentals — how training data quality affects model performance, common failure modes from bad/biased data, and how to evaluate a model's output critically
- Hands-on experience training, fine-tuning, or updating ML models — not just applying pre-built tools or doing descriptive analysis
- Strong SQL and Python skills (pandas, numpy, scikit-learn, or a deep learning framework such as PyTorch/TensorFlow); comfortable exploring and cleaning large, messy datasets independently
- Practical experience working with AI coding tools (e.g., Copilot, Cursor, Claude Code, or similar) as part of your daily workflow, with an agentic mindset — comfortable delegating well-scoped subtasks to AI tools/agents, verifying their output, and iterating quickly rather than hand-coding everything from scratch
- Ability to translate ambiguous questions into measurable, trackable metrics
- Familiarity with data labeling or annotation workflows is a plus, not required
- A quality-first, curious mindset — interested in why data issues occur, not just flagging them
- Exposure to computer vision or video/image datasets specifically is a plus

Success Looks Like

- Measurable improvement in data quality and coverage over time
- Clear, trusted quality benchmarks that inform data and modeling decisions
- Strong collaboration with engineering on data pipeline health

Base Salary range of $121,000 - $150,000 DOE + bonus target up to 20% + equity

## About wyzecam.com

## Company Overview
- **One-liner**: Wyze makes affordable smart home security cameras and devices, aiming to democratize access to smart home technology.
- **Entity Type**: Private (Series B, $155M total funding)
- **Headquarters**: Kirkland, Washington, United States
- **Founded**: 2017
- **Founders**: Yun Zhang, Dongsheng Song, Dave Crosby, Elana Fishman

## Core Business
- Primary industry: Smart Home Technology / Consumer Electronics
- Target customers: B2C (homeowners, renters, small businesses)
- Mission statement: "Be Friends With Users" — to make great technology accessible to everyone through an affordable smart home platform.

## Products & Services
- **Wyze Cam (various models)**: Indoor/outdoor security cameras with HD video, night vision, motion alerts, and AI features (e.g., Solar Cam Pan 2K, Window Cam, Duo Cam Pan). Type: Hardware + SaaS.
- **Video Doorbell**: Battery-powered doorbell camera with color night vision and microSD storage. Type: Hardware.
- **Wyze Lock Bolt v2**: Smart lock with fingerprint recognition, BHMA Grade 2 security, and 8-month battery life. Type: Hardware.
- **Wyze Home Monitoring**: 24/7 professional home security monitoring system. Type: Service.
- **Wyze BodyScan**: AI-powered health/body analysis device. Type: Hardware + AI.
- **Wyze App**: Central app for device control, livestreams, and AI chat agent. Type: Mobile App / Platform.

## Market Standing
- **Valuation**: Not publicly disclosed (last Series B in 2021)
- **Key Metric**: Annual Revenue ~$61.1M (latest estimate); Total Funding $155M
- **Notable Investors/Partners**: Norwest Venture Partners (lead investor in Series A), Marcy Venture Partners (lead in Series B), and others.
- **Growth Signals**: Trusted by over 12 million households; named one of *Time* magazine’s most influential companies of 2022; 152 employees (+12.9% YoY); strong talent pipeline from Amazon, Microsoft, and Google.

## Competitive Advantages
- **Radical affordability**: Products priced dramatically below competitors (e.g., first camera launched at $19.99 vs. ~$200 for comparable brands).
- **Customer-centric philosophy**: "Be Friends With Users" drives product development, pricing, and support transparency.
- **Integrated AI**: In-house AI for person tracking, smart alerts, and health analysis, differentiating from basic camera vendors.
- **Large installed base**: Over 12 million households create a strong ecosystem lock-in and data advantage for AI improvements.

## Strategic Focus
- **Expanding the smart home ecosystem**: Adding new product categories (e.g., BodyScan, smart locks, home monitoring) to deepen customer relationships.
- **AI and subscription growth**: Pushing AI-powered features and subscription services (e.g., Home Monitoring, Cam Plus) for recurring revenue.
- **International expansion**: Growing presence beyond the US (offices in China, Canada, Philippines, Switzerland).
- **Product innovation**: Continuing to launch "too good to be true" products that disrupt price/performance norms.

## Why Work Here
- **Culture**: Described as rooted in relationships, transparency, and authenticity. Co-founders came from Amazon and brought customer-obsession principles. Voted one of the best places to work in Seattle.
- **Perks**: 100% paid employee premiums for benefits (family coverage partially covered); 24 days of PTO; 12 holidays (8 set + 4 floating); free product selection for new hires; employee discounts.
- **Work Environment**: Hybrid/office presence in Kirkland, WA (multiple offices in the area). Global team across 6 countries.
- **Engineering Culture**: Strong technical team (45% of staff in technical roles). Emphasis on AI, cloud platform, and hardware-software integration. Notable alumni from Amazon, Microsoft, Google.
- **Growth**: 12.9% YoY headcount growth with active hiring in product management, software engineering, supply chain, and finance.
- **Considerations**: Employer rating is 2.9/5 (80 reviews) with lower scores for work-life balance (2.5) and compensation (2.5) — may indicate high pressure or below-market pay relative to Big Tech.

## Sources
1. [wyze.com - Careers](https://www.wyze.com/pages/careers)
2. [linkedin.com/company/wyzelabs](https://linkedin.com/company/wyzelabs)
3. [wyze.com - Official Site](https://www.wyze.com/)
4. [global.wyze.com - About Wyze](https://global.wyze.com/en-co/pages/about-wyze)
5. [cbinsights.com - Wyze Labs](https://www.cbinsights.com/company/wyze-labs)

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