Data Science Engineer

Adobe

Data Science Engineer at Adobe focused on developing predictive techniques for forecasting retention metrics. Collaborating with finance and stakeholders for data insights and process enhancements.

Posted 7/24/2026full-timeSan Jose • California, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $133,100 - $236,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in SQL and Python for data analysis and modeling, with a strong understanding of machine learning techniques for time-series analysis. Experienced in automating and enhancing forecasting processes while collaborating with finance and business stakeholders to derive actionable insights.

Highest-signal resume keywords

SQL ProficiencyPython ProficiencyMachine Learning TechniquesData Visualization ToolsData Cloud Platform Experience

ATS Keywords

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Hard Skills

SQLPythonMachine LearningData AnalysisForecastingData ModelingStatistical AnalysisData AutomationCohort AnalysisTime-Series Analysis

Soft Skills

Creative ThinkingProblem-SolvingIntellectual CuriosityCommunication SkillsCollaboration

Tools & Technologies

Power BITableauDatabricksAWSSnowflakeMicrosoft OfficePower QueryM/DAXGitHub

Industry Keywords

Financial Planning and AnalysisData ScienceForecasting ProcessOperational ProblemsData StructuresAnalytic ApplicationsBusiness InsightsData EngineeringCustomer Cancellation ForecastingCohort Retention

Tech Stack

Tools & technologies

AWSCloudPythonSQLTableau

About the role

Key responsibilities & impact

A Finance Data Scientist within Adobe’s Creativity & Productivity FP&A (Financial Planning and Analysis) team partners with finance and business stakeholders to understand, and then develop and enhance the existing or proposed forecasting process, optimizing and refining by leveraging automation and AI/ML techniques.
Drive data science modeling initiatives for forecasting and analysis
Automate, enhance, and maintain analytic applications and data structures used for modeling and forecasting
Monitor weekly performance, understand the root causes of changes in metrics, and continually keep an eye on how to continuously “Create the Future” and further enhance forecast algorithms
Work with the PowerBI team to deliver requirements to create and maintain dashboards tracking key indicators
Partner with Finance and other teams to build data science models to solve a wide breadth of business challenges
Analyze business or financial data to provide insights to the finance leadership team on process & system automation opportunities
Analyze data to identify or resolve operational problems to create processes to reverse engineer existing data flows and source-to-target mappings and work with data engineering teams to implement changes.
Prepare analytical reports to document financial models and data processes.
Demonstrate strong intellectual curiosity towards enhancing current methodologies and processes
Capture, synthesize, and interpret disparate quantitative data within the context of business objectives, identify trends, and explore data through segments and cohorts
Be a change agent, ensuring users adopt new and innovative technologies.

Requirements

What you’ll need

Strong proficiency in SQL and Python; R is a plus.
Experience in data cloud platform (eg. Databricks, AWS, Snowflake)
Understanding of machine learning techniques, specifically involving supervised learning applied to time-series analysis
Proficiency with data visualization tools (e.g. Power BI, Tableau)
Experience exploring large amounts of information, extracting insights, and achieving real-world results
Ability to dig in, understand the data, and to use creative thinking and problem-solving skills are musts
History of deriving and communicating actionable insights from analysis projects to product and/or business leaders
Degree in a quantitative field like statistics, economics, applied math, operations research or engineering preferred, or related work experience
Knowledge of Microsoft Office, specifically Power Query, M/DAX is a plus
Understanding of Version Control frameworks such as GitHub is a plus
Knowledge of customer cancellation forecasting and cohort retention is a plus.

Benefits

Comp & perks

Comprehensive benefits programs