Investment Tech Co-op: Data Pipelines & AI in Finance

wellington

Boston (MA)

On-site

USD 20,000 - 27,000

Part time

6 days ago
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Job summary

Wellington Management in Boston offers a Technology Co-op position that gives hands-on exposure to financial technology within the Science Research Technology team. You will help build data pipelines, onboard datasets, and contribute to investor-facing tools that turn complex data into clear insights for investment research.

The role emphasizes teamwork, learning, and cross-training across functions. You should be proficient in Python and eager to explore data analysis with Pandas and PySpark,

Qualifications

  • Well organized, resourceful, and adaptable to changing priorities.
  • Strong Python programming language knowledge.
  • Nice to have experience with Python data analysis (Pandas, PySpark).
  • Nice to have cloud data solutions on AWS or Azure.
  • Ability to manage multiple priorities and strong analytical skills.
  • Team-oriented with willingness to pitch in.

Responsibilities

  • Partner with data scientists to translate requirements into work items.
  • Participate in technical design of solutions.
  • Develop data pipelines to onboard datasets.
  • Evaluate and onboard alternative datasets, including web-scraped sources.
  • Participate in AI-enabled data analytics projects for investment research.
  • Enable data analysis and data quality using various tools.
  • Test, rollout applications and drive adoption.

Skills

Python
Pandas
PySpark
AWS
Azure
Data analysis

Education

Northeastern University student

Job description

Wellington Management in Boston offers a Technology Co-op position that gives hands-on exposure to financial technology within the Science Research Technology team. You will help build data pipelines, onboard datasets, and contribute to investor-facing tools that turn complex data into clear insights for investment research.

The role emphasizes teamwork, learning, and cross-training across functions. You should be proficient in Python and eager to explore data analysis with Pandas and PySpark,

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