Senior Data Scientist

Publicis Groupe
New York, NY, United States
27 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$125,424.0 - $141,687.0
Working hours
Regular working hours
Job source

Tech stack

Midjourney Amazon Web Services Data Mining Linux Distributed Systems R (Programming Language) Apache Hadoop Statistical Hypothesis Testing Python (Programming Language) Machine Learning SQL Databases Real Time Systems
+6 more
Apache Spark Generative AI Information Technology GPT Data Pipelines Unsupervised Learning

Job description

  • 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.

Requirements

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.

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