Data Scientist, Specialist

Vanguard
Malvern, United States of America
16 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Malvern, United States of America

Tech stack

Microsoft Access
Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Azure
Big Data
Python
Machine Learning
SQL Databases
Cloud Platform System
Feature Engineering
Spark
Model Validation
Jupyter
GIT
Information Technology
Software Version Control

Job description

As a Data Scientist, you will help turn data into decisions by combining strong technical execution with growing business awareness and communication skills. Working alongside more senior data scientists and cross-functional partners, you will contribute to solving real business problems and learn how analytics connects to outcomes.

You'll own well-defined components - a model, a feature pipeline, an analysis - while developing the ability to understand stakeholder needs, ask the right questions, and explain your work clearly so others can act on it. The problems will often arrive partially framed; your role is to execute rigorously while building the judgment to connect technical outputs to business value.

This is a hands-on, growth-oriented role on cross-functional teams where you'll build both technical depth and the communication skills needed to become a trusted analytics partner over time.

What You'll Do

Explain your work clearly to technical and non-technical teammates . Communicate methods, results, and limitations so findings are understood, trusted, and usable in decision-making.

Build well-scoped models and analyses . Develop and validate models on defined problems such as feature engineering, model fitting, calibration, and validation with guidance on approach and standards.

Wrangle and prepare data . Access, transform, clean, and document large-scale data; identify and diagnose inconsistencies and gaps.

Contribute to production . Help deploy and monitor models alongside MLE and engineering, learning the discipline of keeping a live model healthy.

Run experiments others design . Execute designed experiments and analyses correctly and interpret the results.

Explain your work clearly. Communicate methods, results, and caveats to your team so findings can be trusted and built on.

Use AI to work faster . Apply AI coding and analysis assistants to accelerate your own work, while learning to evaluate their output critically.

Learn the practice . Absorb standards and patterns from senior teammates and contribute to a growing, AI-native analytics community.

Requirements

  • 3+ years of data science / ML experience

  • Bachelor's degree in Statistics, Applied Mathematics, Computer Science, Economics, Analytics, or a related quantitative field - or an equivalent combination of training and experience. Grad degree preferred.

  • Working proficiency in Python and SQL and comfort wrangling real, messy data.

  • Solid foundation in statistical and machine learning methods and an understanding of model validation.

  • Exposure to cloud environments (AWS, Azure, or GCP) and standard tooling (e.g., Git, Jupyter ).

  • Clear communication and a strong desire to learn.

Building for the Age of AI, + Project or coursework experience with recommendation, ranking, or decision-support problems.

  • Familiarity with notebooks -to-production workflows and version control.

  • Exposure to big-data frameworks (Spark, etc.).

About the company

We expect this role to use modern AI tools fluently and to grow into building with them. Strength or genuine curiosity in several of the following is what we're looking for: + Working with GenAI / LLMs: comfort using retrieval-augmented generation (RAG), embeddings, and prompting following established patterns. + Building alongside agentic systems: contributing to LLM/agent workflows that someone more senior has architected. + Evaluation basics: helping test model and LLM output against defined quality metrics. + Experimentation fundamentals: understanding the difference between what predicts an outcome and what changes it. + AI-augmented working style: using AI coding assistants to move faster while sanity-checking their output rather than trusting it by default., About Vanguard At Vanguard, we don't just have a mission-we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience., Vanguard, one of the world's leading investment management companies, serves individual investors, institutions, employer-sponsored retirement plans, and financial professionals. We have a diverse and talented crew with a culture that promotes teamwork, along with an unwavering focus on serving our clients' best interests. This website uses "cookies" to distinguish you from other users. A cookie is a small file of letters and numbers placed on your computer or device. This helps us to provide you with a good experience when you browse our website and also allows us to improve our site and services. The cookies are stored locally on your computer or mobile device. To accept cookies you can continue browsing as normal. Or you can go to ourPrivacy Policy (https://www.vanguardjobs.com/site-privacy-policy/) to read more information and learn how to change your preferences. Read More

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