Data Science Engineer

Jobtailor; California (MO); On-site; USD 120,000 - 170,000; Full time

Job summary

Adobe’s Finance Data Scientist role focuses on partnering with FP&A and business stakeholders to forecast, analyze, and optimize processes using automation and AI/ML. You will drive data science initiatives for forecasting and analytics, automate analytic apps, and collaborate with the Power BI team to deliver dashboards for key indicators.

The position emphasizes exploring large data sets, deriving actionable insights, and communicating results to senior leadership while advancing forecasting

Qualifications

• Strong proficiency in SQL and Python; R is a plus.
• Experience in data cloud platform (e.g. Databricks, AWS, Snowflake).
• Understanding of machine learning techniques, specifically supervised learning for time-series analysis.
• Proficiency with data visualization tools (Power BI, Tableau).
• Experience exploring large datasets to derive actionable insights.
• Ability to understand data and solve problems with creative thinking.

Responsibilities

• Partner with finance and business stakeholders to forecast and analyze data.
• Build and refine forecasting processes using automation and AI/ML.
• Automate, enhance, and maintain analytic apps and data structures for modeling.
• Monitor weekly performance and investigate root causes of metric changes.
• Deliver dashboards with requirements to track key indicators (Power BI/Tableau).
• Work with data engineering to implement data flow changes (source-to-target).
• Prepare analytical reports documenting financial models and data processes.
• Capture and interpret disparate data within business context to identify trends.

Skills

SQL Proficiency

Python Proficiency

Machine Learning Techniques

Data Visualization Tools

Data Cloud Platform Experience

Time-Series Analysis

Cohort Analysis

Problem-Solving

Communication Skills

Education

Quantitative degree

Tools

Databricks

AWS

Snowflake

Power BI

Tableau

Power Query

M/DAX

GitHub

Job description

• 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

• 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.

Core Competencies

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 Proficiency
• Python Proficiency
• Machine Learning Techniques
• Data Visualization Tools
• Data Cloud Platform Experience

ATS Optimization Keywords

Hard Skills

• SQL
• Python
• Machine Learning
• Data Analysis
• Forecasting
• Data Modeling
• Statistical Analysis
• Data Automation
• Cohort Analysis
• Time-Series Analysis

Soft Skills

• Creative Thinking
• Problem-Solving
• Intellectual Curiosity
• Communication Skills
• Collaboration

Industry Keywords

• Financial Planning and Analysis
• Data Science
• Forecasting Process
• Operational Problems
• Data Structures
• Analytic Applications
• Business Insights
• Data Engineering
• Customer Cancellation Forecasting
• Cohort Retention

Tools & Technologies

• Power BI
• Tableau
• Databricks
• AWS
• Snowflake
• Microsoft Office
• Power Query
• M/DAX
• GitHub