Pay
In line with similar jobs
$150K against $118K–$195K, the middle half of what similar US postings state.
From 3,828 postings in the last year. Stated ranges, not salaries paid.
Jersey City, NJ, US
Actively hiring, first seen by us 4 days agoTo learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. Salary range for the position: $150,000 - $150,000/Yr. The successful candidate may be eligible for an annual discretionary incentive compensation award. The successful candidate may be eligible to participate in the relevant business unit’s incentive compensation plan, which also may include a discretionary bonus component. Morgan Stanley offers a full spectrum of benefits, including Medical, Prescription Drug, Dental, Vision, Health Savings Account, Dependent Day Care Savings Account, Life Insurance, Disability and Other Insurance Plans, Paid Time Off (including Sick Leave consistent with state and local law, Parental Leave and 20 Vacation Days annually), 10 Paid Holidays, 401(k), and Short/Long Term Disability, in addition to other special perks reserved for our employees. Please visit mybenefits.morganstanley.com to learn more about our benefit offerings. Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.Read the full posting
Employment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Develop and deploy machine learning models for client acquisition and targeting
Analyze large, complex datasets to find patterns, correlations and trends
Set up and run large-scale experiments to test hypotheses and grow the business
Support and enhance existing models to improve performance
Translate business needs into analytics solutions with Legal, Compliance and Risk
develop data science solutions that can be tested and deployed to enable data driven recommendations and outcomes
Analyze large, complex datasets to reveal underlying patterns, correlations, and trends quantitatively.
Set up and conduct large-scale experiments to test hypotheses and drive business growth.
Support and enhance existing models to ensure better performance.
Collaborate with cross-functional stakeholders (Legal, Compliance, Risk, Technology, and Business Partners) to translate business needs into analytics solutions
What you’ll bring to the role: -Requires a Master’s in Data Science, Quantitative Economics, Mathematics, or a related field. -Requires two (2) years of experience in the position offered or two (2) years as a Data Science & Analysis Associate, Machine Learning Researcher, or a related role.
Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
In line with similar jobs
$150K against $118K–$195K, the middle half of what similar US postings state.
From 3,828 postings in the last year. Stated ranges, not salaries paid.
Day 4
Early. Similar jobs usually come down between day 8 and day 60.
At Morgan Stanley, jobs usually come down by about day 33.
From 11,783 similar postings that came down, and 206 of Morgan Stanley’s. Coming down is not always a hire.
40 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
-Requires two (2) years of experience with the following skills: * End-to-end development of machine learning solutions by translating business opportunities into production-grade models and pipelines including data sourcing, feature engineering, evaluation, deployment, and monitoring with success metrics tied to measurable business outcomes; * Developing and benchmarking algorithms including deep learning approaches for classification and regression, using rigorous experimentation to improve performance and robustness; * Designing and deploying agentic AI solutions and applying generative AI techniques to enhance machine learning and deep learning model performance, robustness, and development efficiency; * Python for predictive modeling, data processing, feature engineering, statistical analysis, and workflow automation; * Writing SQL queries for data extraction, transformation, aggregation, and analysis on enterprise-scale relational databases; * Applying statistical analysis, hypothesis testing, and A/B testing methodologies to evaluate model and business performance; * Applying feature engineering, unsupervised learning methods, text processing, and pattern discovery techniques on structured and unstructured datasets; * Developing reports and visual analytics to communicate model performance, experimental results, and business insights to technical and non-technical stakeholders; and * Partnering with stakeholders to gather requirements, communicate analytical findings and model limitations, document decisions, and support governance processes for production analytics and machine learning solutions; and Validating the machine learning models in collaboration with the validation team to ensure accuracy and reliability of Machine Learning (ML) models.
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New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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Jersey City, NJ, US
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