- Company Name
- Analysis Group
- Job Title
- Senior Data Science Intern (PhD) - Boston (2026 Start Date)
- Job Description
-
**Job Title**
Senior Data Science Intern (PhD)
**Role Summary**
Apply advanced statistical, mathematical, and machine‑learning techniques to complex client problems in finance, health care, energy, and life sciences. Build end‑to‑end data pipelines, production‑grade models, and interactive analytics tools. Drive methodological innovation, mentor junior team members, and disseminate new technologies within the organization.
**Expectations**
- Participate as a core team member on client engagements and research projects.
- Deliver actionable insights that influence strategic decisions.
- Continuously learn and apply cutting‑edge data‑science methods and high‑performance computing solutions.
- Foster internal knowledge sharing through training and documentation.
**Key Responsibilities**
1. Analyze structured and unstructured datasets (e.g., EMR, social media, financial transactions) using advanced statistical and mathematical methods.
2. Design, implement, and deploy end‑to‑end data‑engineering and machine‑learning pipelines in Python, R, or other OO languages.
3. Develop NLP models for processing text data and integrate them into production workflows.
4. Optimize database access and processing of large‑scale data on grid or cloud platforms (Azure, AWS).
5. Create interactive dashboards and visualizations (R/Shiny, Python/Flask, D3) to present findings to clients.
6. Enhance computational efficiency through C/C++/CUDA optimization and HPC best practices.
7. Provide technical training on Linux, Docker, and front‑end frameworks (Vue.js, Angular) to expand the in‑house skill set.
8. Review literature, evaluate emerging tools, and recommend technology adoption to improve service offerings.
9. Collaborate with interdisciplinary teams, ensuring clear communication of methodology and results.
**Required Skills**
- Advanced statistical and mathematical modeling (regression, time‑series, causal inference).
- Proficiency in Python and/or R; experience with data‑science libraries (scikit‑learn, caret, PyTorch, etc.).
- Strong data engineering: ETL, SQL, NoSQL, big‑data frameworks (Spark, Hadoop).
- NLP techniques (tokenization, embeddings, transformers).
- Cloud platform familiarity (Azure, AWS) and HPC usage.
- Linux operating system expertise; Docker containerization.
- Front‑end development with a JavaScript framework (Vue.js, Angular).
- Code optimization in C/C++/CUDA for compute‑heavy tasks.
- Excellent written and verbal communication; ability to translate technical concepts for non‑technical stakeholders.
- Team collaboration and project management experience.
**Required Education & Certifications**
- Current PhD candidacy in Computer Science, Data Science, Statistics, Economics, Mathematics, or a closely related field.
- Minimum of 3+ years of research or industry experience applying advanced analytics.
- Valid U.S. work authorization for internship duration (e.g., F‑1 CPT, J‑1 Academic Training).
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