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) About Bluefish Bluefish believes that AI represents the next major chapter of the internet — and that consumers will increasingly use AI to consume information and media online. On this new AI internet, brands will need new tools and technologies to tell their stories to consumers online, and a new marketing ecosystem will be created around AI. Bluefish is building the platform that helps brands engage consumers on this new AI channel, with powerful enterprise tools to manage AI brand safety and engage consumers with thoughtful and personalized AI marketing experiences. The Bluefish team is a tight-knit group of mar-tech industry veterans who previously helped build foundational ad-tech platforms now owned by Meta and Microsoft. Bluefish, the leading AI marketing platform for the Fortune 500, recently announced a $43 million Series B growth financing co-led by Threshold Ventures and NEA with participation from multiple enterprise investors including Amex Ventures, TIAA Ventures, Salesforce Ventures, and Bloomberg Beta. We are a globally distributed team, with business operations based in New York City and engineering based in Europe and New York. Why Bluefish & Our Values Unique opportunity to join on the ground floor of a fast-moving startup building at the center of AI Tackle challenging and abstract problems while disrupting the $300BN legacy martech industry Join an experienced high-performing team where you will have immediate ownership and impact Experience a true meritocracy with significant career growth upside as the business scales 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

Requirements

Must-haves

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.
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
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)

Nice-to-haves

None flagged.

Application prep

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