Data Science Engineer

Data Science / Forecasting Analyst ABOUT THE TEAM The Digital Media Web Analytics & Data Science team sits at the center of Adobe.com's growth engine. We partner cross-functionally with Finance, Product, Marketing and GTM teams to forecast traffic and conversion, quantify the drivers of growth, and build the analytical and AI-powered tools that help the broader organization make faster, data-backed decisions across Adobe's Digital Products.

We're looking for a Data Science / Forecasting Analyst to join our team and help build and maintain the statistical models, forecasts, and AI-powered tools that guide Adobe.com's traffic and conversion planning. You'll work closely with senior data scientists to gather and analyze data from multiple sources, contribute to the quarterly forecasting and target-setting process, and build LLM-based applications and agents that make insights self-serve for business stakeholders. This is a great opportunity for someone with a strong quantitative foundation and hands-on coding experience who wants to grow into a broader data science and AI-tooling role at scale.

Gather, clean, and analyze data from Adobe Analytics / Customer Journey Analytics (CJA) , Databricks/SQL tables, and other internal sources to support traffic and conversion forecasting for Adobe.com. Build, maintain, and improve Python-based statistical forecasting models across dimensions such as channel, geography, and device. Support the quarterly forecasting and target-setting process, helping scope enhancements and validate forecast accuracy against actuals & financial targets. Conduct performance deep-dives into traffic, conversion, and funnel metrics to diagnose the drivers behind trends and anomalies, and translate findings into clear, actionable stakeholder narratives. Support A/B test design, execution, and analysis — from hypothesis formulation through statistical read-out — to validate growth hypotheses and quantify the impact of website/product changes. Design, prototype, and ship LLM-based applications, chatbots, and AI agents/skills that enable stakeholders to query performance data, generate insights, and automate recurring reporting via natural language. Contribute to anomaly detection frameworks that proactively flag irregularities in traffic and order trends. Automate recurring reporting workflows to reduce manual effort and improve turnaround time for weekly and monthly business readouts. Partner with Finance, Product, and GTM teams to understand business context, gather requirements, and translate analysis into clear, actionable recommendations. Present findings and forward-looking commentary to stakeholders in a clear, structured, and data-driven manner. Continuously evaluate new data sources, tools, and modeling techniques (including applied LLM/GenAI methods) to improve forecasting accuracy and analyst productivity.

Bachelor's/Masters degree in Computer Science, Statistics, Economics, Data Science, Engineering, or another relevant quantitative field. 2-5 years of relevant experience in data analysis, data science, or forecasting — experience in a Web/Digital/GTM environment is a strong plus. Hands-on, production-level proficiency in Python (pandas, NumPy, and standard statistical/ML libraries) and SQL for data extraction, transformation, and analysis. Demonstrated experience building LLM-based applications — e.g., chatbots, AI agents, retrieval-augmented generation (RAG) pipelines, prompt-engineered tools, or automation "skills" — with a portfolio or examples you can walk through. Basic understanding of A/B testing / experimentation design (hypothesis formulation, statistical significance, read-out). Strong analytical and problem-solving skills, with the ability to translate data into a clear narrative for both technical and non-technical audiences. Hands-on experience with ML techniques such as regression and clustering is a good to