Data Scientist - Graduate

NASDAQ
Boston, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior
Compensation
$ 146K

Job location

Remote
Boston, United States of America

Tech stack

Artificial Intelligence
Artificial Neural Networks
Relational Databases
Statistical Hypothesis Testing
Python
Machine Learning
TensorFlow
SQL Databases
PyTorch
Deep Learning
Model Validation
Information Technology
Data Analytics

Job description

  • Establish and maintain clear lines of communication, providing regular updates on project progress, insights, and potential impact on key performance indicators.
  • Present findings and insights to non-technical partners in a clear and understandable manner, encouraging a collaborative environment for informed decision-making.
  • Engage with key stakeholders to understand their business objectives and communicate the value proposition of data science initiatives.

Requirements

  • 1-3 years of experience working as a Data Scientist, ML/AI Engineer or in a similar role
  • Advanced degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or another technical field.
  • Understanding of the fundamentals of Statistics & Machine Learning (hypothesis testing, p-values, confidence intervals, regression, classification, optimization).
  • Demonstrated experience with deep learning (CNNs, RNNs, transformers and other types of Deep Neural Networks) and working knowledge of one of the main deep learning libraries (PyTorch, Tensorflow, Jax)
  • Fluency in Python and SQL or other similar relational database management systems.
  • Excellent verbal and written English skills to guide cross-functional teams on complex data-driven projects.

Nice to have:

  • Work experience in a corporate environment or finance/fintech industry
  • Demonstrated interest in finance and/or market microstructure
  • Industry experience with Deep Learning models and methods (Deep Learning Life cycle - from Problem Definition to Model Evaluation and Monitoring)

This position will be located in Boston and offers the opportunity for a hybrid work environment at least 3 days a week in-office, subject to change, providing flexibility and accessibility for qualified candidates.

Applicants must be authorized to work in the United States without the need for employment-based visa sponsorship now or in the future. Nasdaq will not sponsor applicants for employment-based visa status for this position.

Benefits & conditions

Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities.

We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated.

We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.

What We Offer

We're proud to offer a competitive rewards package that is meaningful, recognizes the unique needs of our employees and their families and incentivizes employees for their contribution to Nasdaq's overall success.

The base pay range for this role is $86,000 - $146,000. In addition to base salary, Nasdaq provides a generous annual bonus/commission (short-term incentive), and equity (long-term incentive), comprehensive benefits, and opportunity for growth. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, business needs and market demands.

Nasdaq's programs and rewards are intended to allow our employees to:

  • Secure Wealth: 401(k) program with 6% employer match, Employee Stock Purchase Program with 15% discount, Student loan repayment program up to $10k, Company paid life and disability plans, Generous paid time off
  • Prioritize Health: Comprehensive medical, dental and vision coverage, Health spending account with employer contribution, Paid flex days to support mental wellbeing, Gym membership discounts
  • Care for Family: Hybrid home/office schedule (for most positions), Paid parental leave, Fertility benefits, Paid bereavement leave
  • Connect with Community: Company gift matching program, Employee resource groups, Paid volunteer days
  • Grow Career: Education Assistance Program, Robust job skills training and Professional development opportunities

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