Data Scientist

About the position

The Data Scientist at Digitas is responsible for transforming raw data into actionable insights through advanced analytics and data engineering techniques. This role involves developing automated data pipelines, conducting exploratory analyses, and applying machine learning techniques to enhance marketing strategies and business outcomes. The Data Scientist will work closely with the analytics team to interpret large datasets and provide recommendations that align with business goals.

Responsibilities

• Develop and implement analytics applications to transform raw data into meaningful information.
• Translate marketing and business questions into data queries.
• Provide product insights and analytics solutions, designing fully automated data pipelines.
• Conduct exploratory analysis to identify relevant insights and useful transformations.
• Apply quantitative techniques to uncover latent patterns in the data.
• Interpret data, analytical results, and visuals to generate conclusions and recommendations.
• Test scalable data pipelines or models for real-time applications.
• Ensure analytic tasks and results meet established objectives and timelines.
• Connect business goals with Multi-Touch Attribution (MTA) model results.
• Analyze log-level data and provide customer journey analysis insights and evaluations of media channel performance.
• Develop and implement multi-faceted solutions for complex marketing and business challenges.
• Involved in data engineering and data cleansing techniques to ensure data quality using Google Cloud platform and SQL techniques.
• Build new models and apply advanced analytics using machine learning techniques.
• Build new customer states by accessing trends through market research and presenting results using Tableau.
• Guide analytics team to interpret large data and recommend analytical solutions.

Requirements

• Master's degree in Computer Science, Data Science, Engineering, Marketing, or a related field.
• Two years of experience in the job offered or in a related occupation.
• One year of experience building propensity models using Python.
• One year of experience analyzing log-level data with R under the AWS framework.
• One year of experience utilizing SQL and Google Cloud platforms for data engineering and data cleansing techniques.
• One year of experience building new models and applying advanced analytics using machine learning techniques.
• One year of experience using Tableau to build new customer states and presenting results.
• One year of experience interpreting large data using SQL.

Benefits

• Medical coverage
• Dental insurance
• Vision insurance
• Disability insurance
• 401K
• Parental leave
• Family care leave
• Family forming assistance
• Tuition reimbursement
• Flexible time off