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Data Scientist - Graduate

Nasdaq

Boston, Cayman Islands (Hybrid) ・ フルタイム

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経験
1~3歳
給料
USD 86,000 – USD 146,000 / year
求人情報
1
投稿済み
2時間前
作業モード
ハイブリッド
教育
Advanced degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or another technical field
資格
Candidates must be authorized to work in the United States without needing current or future employer-sponsored visa sponsorship. Applicants from all backgrounds and identities are welcome; reasonable accommodation is available for candidates with disabilities.
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勤務地

仕事内容

Role overview

Nasdaq is looking for a graduate-level Data Scientist to join its team in Boston. This role is designed for someone at the start of their data science career who wants to learn, collaborate, and contribute to work that supports complex datasets used in global financial markets.

You do not need to have every skill from day one; the company emphasizes learning, teamwork, and innovation, and will support your growth, confidence, and professional network.

What you'll do

  • Develop, investigate, and design AI/ML solutions for use across the organization.
  • Keep project stakeholders informed with regular progress updates, key insights, and possible effects on business metrics.
  • Translate technical results into clear explanations for non-technical partners and support collaborative decision-making.
  • Work closely with stakeholders to understand business goals and communicate how data science work creates value.

Required background

  • 1 to 3 years of experience in data science, machine learning, AI engineering, or a closely related role.
  • An advanced degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or another technical discipline.
  • Strong understanding of statistical and machine learning concepts such as hypothesis testing, p-values, confidence intervals, regression, classification, and optimization.
  • Practical exposure to deep learning, including models such as CNNs, RNNs, transformers, and other neural network approaches.
  • Working knowledge of a major deep learning framework such as PyTorch, TensorFlow, or JAX.
  • Strong command of Python and SQL, or comparable relational database systems.
  • Excellent spoken and written English for guiding cross-functional teams through complex, data-driven work.

Preferred experience

  • Prior exposure to a corporate setting or to the finance/fintech sector.
  • Interest in finance and/or market microstructure.
  • Hands-on experience with deep learning model lifecycles, from defining the problem through evaluation and monitoring.

Work arrangement and eligibility

This is a Boston-based position with a hybrid schedule requiring at least 3 days per week in the office, although the arrangement may change.

Only candidates authorized to work in the United States without current or future employer-sponsored visa support can be considered. Nasdaq will not provide visa sponsorship for this role.

Inclusion and equal opportunity

Nasdaq welcomes applicants from all backgrounds and identities and is committed to maintaining an inclusive workplace. Reasonable accommodation is available for candidates with disabilities during the hiring process.

Compensation and rewards

The base salary range for this role is USD 86,000 to 146,000 per year. In addition to base pay, the role includes a generous annual bonus/commission opportunity, equity, comprehensive benefits, and room for career growth. Final compensation may vary depending on skills, experience, education or training, business needs, and market conditions.

Benefits and perks

Nasdaq offers a broad rewards package that includes retirement, health, family, community, and career-development support.

  • 401(k) plan with a 6% employer match.
  • Employee Stock Purchase Program with a 15% discount.
  • Student loan repayment support of up to USD 10,000.
  • Company-paid life and disability coverage.
  • Generous paid time off.
  • Comprehensive medical, dental, and vision insurance.
  • Health spending account with employer contribution.
  • Paid flex days for mental wellbeing.
  • Gym membership discounts.
  • Hybrid home/office schedule for most positions.
  • Paid parental leave.
  • Fertility benefits.
  • Paid bereavement leave.
  • Gift matching program.
  • Employee resource groups.
  • Paid volunteer days.
  • Education assistance program.
  • Job skills training and professional development opportunities.

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