Data Scientist Job at Beezwax Datatools (Cupertino)

Job Description

The Marketing Data Scientist sits at the intersection of data, AI, and marketing strategy — partnering with leadership to evaluate campaign effectiveness, uncover growth opportunities, and build scalable analytical solutions for payments & digital cash products.

Job Responsibility

Analyze marketing and business performance using SQL, Python, and statistical methods to surface actionable insights and inform optimization strategy.
Design and execute A/B tests, multivariate experiments, and causal inference analyses to measure campaign effectiveness.
Develop and deploy AI/ML models (e.g., customer segmentation, churn prediction, recommendation systems, marketing optimization) to enhance targeting, personalization, insights discovery, and decision-making.
Integrate machine learning insights into existing business workflows to enable automation and real-time optimization of marketing programs.
Partner with marketing leaders as a trusted thought partner, advising on campaign design, measurement frameworks, and data-driven storytelling.
Communicate insights through clear and visually compelling presentations using Keynote, Tableau, or other visualization tools.
Collaborate cross-functionally with engineering, product, and finance teams to ensure data accuracy, scalability, and accountability towards business impacts.

Requirements

3+ years of experience in data science, marketing analytics, or related quantitative fields applied in a business, preferably Enterprise, context.
Proven expertise with large, complex datasets and transforming data into actionable business insights.
Demonstrated ability to understand complex business data end-to-end, from raw data to insight, and communicate findings effectively to both technical and non-technical audiences.
Proficiency in SQL and Python (including libraries such as pandas, scikit-learn, casualimpact, statsmodels, LLMs packages like GPT, Claude, etc.).
Strong understanding of AI/ML techniques, including regression, classification, clustering, segmentation, and predictive modeling, deep learning models, and LLMs.
Experience integrating machine learning outputs into marketing or business processes to drive automation and performance.
Skilled in experimental design, significance testing, and multivariate analysis.
Excellent data storytelling and visualization abilities, translating technical findings into clear business recommendations.
Outstanding verbal and written communication skills
ability to influence and build trust across functions.
Advanced degree (Master's or Ph.D.) in Data Science, Statistics, Economics/Econometrics, Computer Science, Marketing Science, Operations Research, Mathematics, or Engineering — completed or in progress.

What we offer

Competitive compensation
Healthcare package with vision and dental
Vacation / PTO
Retirement plan
Support for your continued learning and professional development
Hardware and software
Office in Cupertino, CA

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