Senior Data Scientist

Digitas North America; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Digitas North America is seeking a Senior Data Scientist to solve complex marketing and business challenges by accessing, integrating, and modeling diverse data sources. You will apply statistical and machine learning methods to derive actionable insights and support strategy in a fast-paced environment.

The role requires strong proficiency in Python or R, SQL, and distributed systems, plus the ability to communicate results to both technical and non-technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field such as statistics, mathematics, econometrics, data science, computer science or related.
• 3+ years of professional data science or analytics experience.
• Experience with statistical or ML methods: descriptive stats, hypothesis testing, dimensionality reduction, feature transformation, supervised/unsupervised learning.
• Experience using Python or R, SQL, and distributed computing systems (Hadoop, AWS).

Responsibilities

• Translating and reframing marketing and business questions into analytical plans.
• Using distributed computing systems to ingest, access and integrate disparate big data sources.
• Conducting extensive exploratory analysis to identify relevant insights, useful transformations and analytical applications.
• Applying quantitative techniques, including statistical and machine learning, to uncover latent patterns in the data.
• Building and testing scalable data pipelines or models for real-time applications.
• Summarizing, visualizing, communicating and documenting analytic concepts, processes and results for technical and non-technical audiences.
• Collaborating with internal and external stakeholders to establish clear analytical objectives, approaches and timelines.
• Sharing knowledge, debating techniques, and conducting research to advance the collective knowledge and skills of our Data Science practice.

Skills

Statistical analysis

Machine learning

Data mining

Python

R

SQL

Distributed computing concepts

Education

Bachelor's or Master's in a quantitative field

Tools

Hadoop

AWS

Spark

Linux

Job description

Company Description
Digitas is the Networked Experience Agency, built on the vision that we create magnetic experiences that earn the right for brands to exist in human networks. Today, and tomorrow. We deliver Networked Experiences by leveraging comprehensive data, technology, creative, media and strategy capabilities. Digitas delivers ambitious outcomes via unique solutions that include Creative Experiences, Integrated Media, Addressable Relationships, Social Marketing and Total Commerce. Celebrated by AdAge as Data and Insights Agency of the Year, U.S Campaign’s Brand Experience Agency of the Year, Media Network of the Year and celebrated by Forrester and Gartner, Digitas serves the world’s leading brands through a global network comprised of more than 5,500 employees across over 65 offices in 43 countries.

Company Description

Digitas is the Networked Experience Agency, built on the vision that we create magnetic experiences that earn the right for brands to exist in human networks. Today, and tomorrow. We deliver Networked Experiences by leveraging comprehensive data, technology, creative, media and strategy capabilities. Digitas delivers ambitious outcomes via unique solutions that include Creative Experiences, Integrated Media, Addressable Relationships, Social Marketing and Total Commerce. Celebrated by AdAge as Data and Insights Agency of the Year, U.S Campaign’s Brand Experience Agency of the Year, Media Network of the Year and celebrated by Forrester and Gartner, Digitas serves the world’s leading brands through a global network comprised of more than 5,500 employees across over 65 offices in 43 countries.

The Digitas culture is made up of fearless, inventive and generous Unicorns of all kinds.

Overview

As a Senior Data Scientist, you’ll solve complex marketing and business challenges—from cross-channel media and customer experience optimization to segmentation, targeting and business strategy—by accessing, integrating, manipulating, mining and modeling a wide array of data sources.

Job Responsibilities

• Translating and reframing marketing and business questions into analytical plans.
• Using distributed computing systems to ingest, access and integrate disparate big data sources.
• Conducting extensive exploratory analysis to identify relevant insights, useful transformations and analytical applications.
• Applying quantitative techniques, including statistical and machine learning, to uncover latent patterns in the data.
• Building and testing scalable data pipelines or models for real-time applications.
• Summarizing, visualizing, communicating and documenting analytic concepts, processes and results for technical and non-technical audiences.
• Collaborating with internal and external stakeholders to establish clear analytical objectives, approaches and timelines.
• Sharing knowledge, debating techniques, and conducting research to advance the collective knowledge and skills of our Data Science practice.

Role

We’re looking for rigorous analytic training and 3+ years professional experience in a data science or analytics role, which typically includes:

• A Bachelor’s or Master’s degree in a quantitative field such as statistics, mathematics, econometrics, operations research, data science, computer science, engineering, marketing or social science methods.
• Hands-on experience mining data for decision-focused insights.
• Hands-on experience running common statistical or machine learning procedures, such as descriptive statistics, hypothesis testing, dimension reduction, feature transformation, supervised or unsupervised learning.
• Hands-on experience using Python or R, SQL, and distributed computing systems such as Hadoop or AWS. Familiarity with Linux and/or Spark preferred.
• Demonstrated interest in marketing analytical applications.
• Demonstrated self-starter who thrives in a fast-paced environment with flat structure.
• Familiarity with prompt-based interaction and commonly used generative AI tools (e.g., ChatGPT, Google Gemini, DALL·E, Midjourney) is a plus, especially for tasks like ideation, research, or content generation.