Data Scientist

RR Donnelley

Data Scientist building marketing machine-learning models and scalable pipelines for RRD, a global marketing, packaging, print, and supply-chain solutions provider. Productionizing analytics, automating modeling workflows, and presenting research-driven recommendations.

Posted 8/14/2026full-timeRemote • Illinois • 🇺🇸 United StatesJuniorMid-Level💰 $128,597 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and implementing machine learning models and data analytics applications, with a strong focus on data transformation, feature extraction, and automation. Proficient in utilizing cloud services and data visualization tools to enhance decision-making and improve product performance.

Highest-signal resume keywords

Machine Learning Model DevelopmentData Pipeline DevelopmentProgramming in Java, Python, and Shell ScriptingData Visualization with Tableau and AWS QuickSightExperience with AWS Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisFeature EngineeringProbability and StatisticsAgile MethodologyData ExplorationData VisualizationHyperparameter TuningProgramming in PythonProgramming in Java

Soft Skills

CollaborationCommunicationPresentation Skills

Tools & Technologies

PostgreSQLMySQLTableauAWS QuickSightPentahoSnowflakeAWS RedshiftHadoopJenkinsGit

Certifications & Qualifications

Master’s Degree in Data ScienceMaster’s Degree in Computer Science

Industry Keywords

Data ScienceData EngineeringAnalytics ApplicationsCloud ServicesAI Processes

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudHadoopJavaJavaScriptJenkinsMySQLPostgresPySparkPythonShell ScriptingSQLTableau

About the role

Key responsibilities & impact

Develop and implement techniques and analytics applications to transform raw data into meaningful information
Build and evaluate marketing machine learning models using first- and third-party customer data
Create and manage end-to-end projects, including analysis design, execution, and summarization of results
Develop scalable data pipelines for feature extraction using cloud services
Identify, clean, analyze, and summarize data from disparate and complex sources
Prototype and implement advanced solutions to improve existing machine learning model performance
Document research plans, results, and conclusions
Present research findings and recommendations to audiences with varying levels of experience
Collaborate with data engineering and operations teams to productionize work
Automate recurring analyses and model-building activities
Participate in planning, roadmap, and architecture discussions to evolve AI processes and improve revenue-generating products

Requirements

What you’ll need

Master’s degree in Data Science, Computer Science, or a related field
Two years of experience in a computer occupation
Two years of experience with programming and data analysis using Java, Python, Shell Scripting, PySpark, or SAS SQL
Experience with PostgreSQL or MySQL
Experience with Tableau, AWS QuickSight, JavaScript, matplotlib, and seaborn
Experience with Pentaho, Snowflake, AWS Redshift, or Hadoop
Experience with AWS services including S3, RDS, SageMaker, Lambda, Step Functions, or Athena
Experience with supervised learning, unsupervised learning, feature engineering, or hyperparameter tuning
Experience with probability and statistics
Experience with Agile methodology
Experience with Jenkins or Git for version control
Experience with data exploration and data visualization
Ability to work 40 hours per week, Monday through Friday, 8:30 a.m. to 5:30 p.m.
Successful completion of a pre-employment background and drug screen

Benefits

Comp & perks

Medical coverage
Dental coverage
Vision coverage
Paid time off
Disability insurance
401(k) with company match
Life insurance
Voluntary supplemental insurance coverages
Parental leave
Adoption assistance
Tuition assistance
Employer/partner discounts
Bonus, commission or incentive program may be included in total compensation