- Company Name
- Epsilon
- Job Title
- Intern Program - PhD Data Science Intern
- Job Description
-
Job Title: PhD Data Science Intern
Role Summary:
A 12‑week research‑focused internship within the Decision Sciences team, focusing on real‑world machine learning challenges in digital marketing. Interns conduct independent research, develop and validate models on large‑scale datasets, and present findings to senior data science leaders, with potential production deployment.
Expectations:
- Execute a complete research project addressing a technology or business problem.
- Demonstrate high autonomy in designing experiments, collecting data, building models, and evaluating performance.
- Deliver clear, actionable insights and recommendations to cross‑functional stakeholders.
- Collaborate with team members for mentorship, peer review, and integration of work into the personalization platform.
Key Responsibilities:
- Apply advanced statistical and machine learning techniques to large anonymized consumer data.
- Design, implement, and tune predictive models using Python, Scala, SQL, or R.
- Optimize model performance through rigorous evaluation and validation.
- Explore and experiment with big‑data technologies (e.g., Hadoop, Spark, Cassandra, MPP databases).
- Communicate complex concepts via reports, visualizations, and oral presentations to non‑technical audiences.
- Integrate research outcomes into ongoing projects and potential production workflows.
Required Skills:
- Current enrollment in a PhD program with coursework and research in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
- Proven experience in hypothesis formulation, exploratory data analysis, and model development.
- Strong command of a programming language (Python, Scala, SQL, R).
- Deep understanding of model evaluation metrics and optimization strategies.
- Ability to work independently and manage end‑to‑end research projects.
- Effective written and verbal communication skills, suitable for diverse audiences.
- Experience with distributed data processing frameworks (Hadoop, Spark, Cassandra, or MPP databases) preferred.
Required Education & Certifications:
- PhD candidate in Data Science, Statistics, Computer Science, Mathematics, or a quantitatively rigorous discipline. (No specific industry certifications required.)