Data Scientist Ii Computer Vision

Limited Information Available on Specific Role Search results do not provide details on the exact "Data Scientist II

• Computer Vision" role at the unnamed NYC-based company from the given BuiltInNYC URL. No direct matches appear for this job title, company name, or computer vision focus across listings, which cover unrelated roles in marketing, operations, product, and fintech at companies like Kalshi, Cents, DISCO, Fora, and others. Without the specific posting content, I cannot deliver a comprehensive breakdown tailored to this opportunity. Actionable Next Steps for Young Professionals (18-25) To research and apply effectively:
• Access the Job Directly: Visit the provided URL (https://www.builtinnyc.com/jobs/remote/data-analytics/data-science) immediately to extract details on requirements, responsibilities, and deadlines. Screenshot or note the company name (likely a fintech/AI firm given NYC trends) for targeted research.
• Company Research Framework: | Step | Action | Why It Matters | |------|--------|---------------| |

1. Identify Company | Search LinkedIn/Glassdoor for the employer using job title + "NYC computer vision." | Reveals history, size (e.g., NYC fintechs like Kalshi are fast-growing with 100-200+ employees), and culture (meritocracy, ownership focus). | |
2. Check News/Funding | Use Crunchbase/PitchBook for recent rounds (NYC saw $25.5B VC in 2024, heavy in AI/fintech). | Shows growth; e.g., firms like Fora raised $60M Series B/C in
3. | |
4. Culture Scan | Review Glassdoor/Levels.fyi for remote/hybrid policies (NYC tech often hybrid post-2024). | Aligns with values like "hire talented people, work hard" seen in prediction market leaders. |

• **Tailor for Data Scientist II
• Computer Vision:**
• Skills Priority: Expect Python, TensorFlow/PyTorch, OpenCV for vision models; ML frameworks; data pipelines. Demonstrate via GitHub projects on object detection (YOLO) or segmentation. NYC AI roles emphasize fintech applications like image analysis for fraud/risk.
• Build Portfolio: Create a Kaggle notebook on computer vision (e.g., NYC traffic cams for prediction markets if fintech-related). Quantify impact: "Improved model accuracy 15% via transfer learning."
• Application Process (Standard for BuiltInNYC Tech Roles):

1. Submit resume/cover via URL (1-2 pages, ATS-friendly: keywords like "computer vision," "deep learning").
2. LinkedIn profile optimization (add skills endorsements).
3. Expect HackerRank/OA: coding (CV tasks), SQL, system design.
4. Interviews: 4-5 rounds (technical: LeetCode medium CV problems; behavioral: "Tell me about a failed model").

• Standout Tips:
• Technical Edge: Know NYC-specifics like AI in fintech (e.g., Bloomberg's data tools). Practice: "How would CV detect anomalies in trading visuals?"
• Soft Skills: Ownership/meritocracy valued; use STAR stories showing initiative.
• Questions to Ask: "How does this role contribute to [company's prediction/AI vision]?" "What CV projects scale next?" Shows research.
• Red Flags to Avoid: Generic resumes; no CV projects; ignoring remote NYC time zone (EST).
• Practical Benchmarks (NYC Data Science, Mid-Level Remote): | Aspect | Range/Detail | |--------|--------------| | Salary | $140K-$180K base + equity (Levels.fyi for DS II; NYC fintech premium). | | Benefits | Health, 401k match, unlimited PTO, learning stipend (common in VC-backed like Kalshi). | | Duration | Full-time (not internship); start flexible, often Q2/Q3. | | Networking | Join NYC Tech Slack/Columbia/NYU AI clubs; alumni via LinkedIn (search "Kalshi data scientist"). | Leverage NYC's AI/fintech ecosystem (549K tech workers, top unis). Apply to similar roles at Kalshi (prediction markets, hard problems) or Capital One (data-heavy) for practice. Update me with the company/job details from the URL for precise intel.