Senior/Staff Data Scientist, Analytics

Bluefish Labs; New York (NY); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Bluefish Labs is seeking a Senior or Staff Data Scientist in New York City to lead analytics initiatives. This role involves owning experiments, providing deep data insights, and fostering a robust analytics practice across the organization.

Ideal candidates will have strong skills in SQL and Python, extensive statistical knowledge, and a proven ability to communicate complex analyses effectively. The position follows a hybrid work model.

Qualifications

• Strong SQL and Python skills.
• Deep statistics background, including hypothesis testing and causal inference.
• Experience designing and operating experimentation frameworks.
• Strong analytical and problem-solving abilities.
• Business acumen to translate findings into actionable narratives.
• Excellent communication skills for technical and non-technical audiences.
• Experience with LLM or AI product data is a plus.
• Familiarity with supervised and unsupervised learning techniques.
• Some experience supporting ML model deployments.
• Comfort reading NLP/ML research papers.
• Experience with BI/visualization tools.

Responsibilities

• Own experimentation end-to-end, including design and analysis of A/B tests.
• Drive causal inference work to understand product outcome mechanisms.
• Serve as the analytics escalation point for deeper statistical problems.
• Build and maintain methodological standards for statistical methods.
• Produce internal research papers and contribute to external analyses.
• Support ad-hoc data requests with fast turnaround.

Skills

SQL

Python

Statistical analysis

Causal inference

Communication

Data preprocessing

Feature engineering

Model evaluation

BI tools

Job description

About the Position

As a Senior or Staff Data Scientist focusing on Analytics, you'll serve as the statistical backbone of Bluefish’s Data Science team. You'll own experimentation and causal inference frameworks, produce rigorous methodological work, and function as the key escalation point for data-driven decision-making across the organization.

You'll collaborate closely with Data Analysts, Applied Researchers, and cross-functional stakeholders — including Product, Marketing Strategy and Services, and Operations — to deliver insights, harden the metrics we report, and deepen the capabilities of our platform.

This role presents a greenfield opportunity to help define Bluefish's data science practice from the ground up, with direct impact on both our internal operations and the analytics products we deliver to customers.

This role is based in our NYC office and follows a hybrid working policy with 3 days in office.

What You'll Be Doing

• Own experimentation end-to-end — design, execute, and analyze A/B tests and other experiments; define statistical significance frameworks
• Drive causal inference work — lead analyses that go beyond correlation to understand the mechanisms behind product and customer outcomes
• Serve as the analytics escalation point — be the go-to resource across the org when problems require deeper statistical rigor
• Build and maintain methodological standards — document and review statistical methods used across the team; ensure analytical quality and reproducibility
• Produce research — author internal research papers, benchmark studies, and methodology documentation; contribute to external-facing analyses (e.g., vertical benchmarking, state of AI)
• Support ad-hoc deep-dives — respond to data requests from RevOps, MSS, Operations, and leadership with fast turnaround and clear narrative

Qualifications

• Strong SQL and Python skills — you write production-quality queries and analytical scripts
• Deep statistics background — hypothesis testing, confidence intervals, power analysis, causal inference
• Extensive experience designing and operating experimentation frameworks at scale
• Strong analytical and problem-solving abilities, with experience in data preprocessing, feature engineering, and model evaluation
• Business acumen — you translate analytical findings into clear, actionable narratives for non-technical stakeholders
• Excellent communication and narrative crafting skills, with the ability to explain complex methods to product, sales, and executive audiences
• Experience working with LLM or AI product data is a strong plus
• Familiarity with supervised learning techniques (e.g., regression, classification, gradient boosting) for predictive analytics use cases
• Exposure to unsupervised learning methods (e.g., clustering, dimensionality reduction) for customer segmentation or behavioral analysis
• Some experience working alongside or supporting ML model deployment — understanding inference pipelines, feature stores, or model monitoring
• Comfort reading and interpreting NLP/ML research papers to stay current on methodological advances relevant to our data
• Experience with BI/visualization tools (e.g., Looker, Omni, Tableau)

Our Values:

• Demonstrated grit and resourcefulness — you find creative solutions, adapt quickly, and aren't afraid to roll up your sleeves in a fast-paced, evolving environment
• Thoughtful and strategic thinker with the ability to anticipate needs, ask the right questions, and deliver insights that truly drive value
• Proven ability to collaborate across functions and roles, fostering open communication and shared ownership of outcomes
• Commitment to craftsmanship — you take pride in delivering high-quality work, paying attention to the small details while keeping the big picture in mind
• Self-starter with a proactive mindset and a strong sense of accountability — able to drive projects forward independently while staying aligned with team goals
• Comfortable navigating ambiguity and learning new tools, processes, or technologies to get the job done