Senior Data Scientist

Job not on LinkedIn

🕒 August 8, 2025

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Bluefish AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

Artificial Intelligence • B2B • SaaS

Bluefish AI is a technology company that specializes in developing advanced artificial intelligence solutions to enhance decision-making processes and improve efficiency across various sectors. The company utilizes innovative algorithms and machine learning techniques to provide data-driven insights and automated solutions for businesses.

📋 Description

• Independently lead end-to-end data science projects: from problem definition and hypothesis generation to modeling, testing, and deployment. • Own your pipeline: design, build, and maintain scalable data workflows and ML systems without needing support from product and engineering teams. • Drive customer-focused experimentation: design A/B tests and other experiments with a clear focus on improving user experience and product outcomes. • Identify new opportunities for research and experimentation—bring forward your own ideas, test them quickly, and evaluate business impact. • Collaborate cross-functionally, especially with engineering, product, and design, while taking full ownership of your project’s goals, execution, and delivery. • Translate data into strategy: craft clear, actionable insights that directly inform product development and company direction. • Stay hands-on with cutting-edge tools and models, particularly LLMs and generative AI, and integrate them into production systems when they solve real problems.

🎯 Requirements

• 5+ years of experience in data science, with a track record of leading and delivering impactful, production-level projects. • Demonstrated ability to work independently: proactively identify problems, design solutions, and push projects forward with minimal oversight. • Strong experience with full-stack data science: data wrangling, modeling, validation, deployment, and monitoring. • Comfortable setting up your own experiments, pipelines, and direction while ensuring alignment with customer and business goals. • Experience working with LLMs or generative AI in real-world applications. • Proficient in Python, SQL, and ML frameworks (e.g., Pandas, Scikit-learn, PyTorch, Hugging Face, LangChain, spaCy/NLTK). • Deep understanding of experimentation techniques: A/B testing, causal inference, and how to interpret results in a business context. • Ability to balance scientific rigor with business pragmatism—understanding which experiments are worth running and which aren’t. • Excellent communication skills and the ability to advocate for data-driven decisions across disciplines. • A mindset of ownership, resourcefulness, and continuous improvement.