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machine learning intern

Uber

<div>We're looking for candidates to intern on the Delivery Logistics team as a PhD Scientist intern during summer 2026 (12 weeks). As an intern, you will be embedded in a product team working on solving real-world Uber problems under the supervision of a scientist on that team, and will have the opportunity to partner closely with Software Engineers, Product Managers, and other cross functional partners.
 
 
About the Role
 
 
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked? If so, Uber is for you. In our Sciences division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
 
 
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
 
 
About the Team
 
 
The Delivery Logistics team builds real-world technology that powers our global marketplace. Our team of scientists works on diverse problems, including building real-time backend matching systems, creating new delightful user experiences, and serving predictions used for decision making across the marketplace.
 
 
In this role, you will use your quantitative skills to generate insights, develop new models, design metrics and run experiments. Uber operates in a constantly-evolving and competitive environment, and our success requires a deep understanding of our marketplace and the ability to build products that scale on a global footprint. You will work on high visibility, high impact projects which have significant impact on Uber's P+L.
 
 
What You'll Do
<ul><li>Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches
</li><li>Work with a cross-functional team to build cutting-edge marketplace products
</li><li>Deploy analysis techniques such as causal inference and funnel analysis to identify our largest business opportunities
</li><li>Work alongside engineers to design and implement production solutions
</li><li>Design and analyze product experiments, and communicate findings and conclusions with stakeholders
</li></ul>Basic Qualifications
<ul><li>Pursuing a PhD specializing in Operations Research, Statistics, Economics, Machine Learning, or other quantitative fields
</li><li>Must have at least one semester/quarter remaining after completion of the internship
</li><li>Experience with exploratory data analysis, statistical analysis and testing, and model development
</li><li>Ability to use Python to work efficiently at scale with large data sets
</li><li>Strong problem solving and analytical abilities
</li></ul>Preferred Qualifications
<ul><li>0-2 years of prior work experience in an analytical setting
</li><li>Organized, detail oriented and able to work independently on multiple projects at once
</li><li>Ability to communicate effectively with both technical and business partners
</li><li>Proficiency with office efficiency tools including email, web browser, web apps, database search, spreadsheets/word processors (Google Apps)
</li><li>Self starter, taking initiative keeping relevant partners in the loop
</li><li>Open to feedback, excellent at implementing newly learned ideas and concepts
</li>Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar) 
<li>
</li></ul> 
 
For New York, NY-based roles: The base hourly rate amount for this role is USD$67.00 per hour. You will also be eligible for various benefits.</div>

2026 PhD Scientist Intern (Delivery Logistics)

Mount Sinai Health System

<div>Description
The Windreich Department of AI &amp; Human Health is rapidly advancing the use of technology to improve health outcomes and is at the forefront of AI implementation within the Mount Sinai Health.
Machine Learning Engineer III will oversee the design and development of sophisticated machine learning systems. They will collaborate closely with cross-functional teams to drive innovation and ensure the successful implementation of machine learning solutions. 
Responsibilities
End-to-End System Responsibility:<ul><li>
Assume complete ownership of the entire machine learning system development process.</li><li>
Coordinate closely with other team members and other engineering teams to ensure seamless integration and alignment with broader organizational goals and workflows.</li><li>
Lead the collaborative efforts with cross-functional teams, including data scientists and product managers, to ensure the successful deployment and robust maintenance of machine learning models.</li><li>
Oversee the continuous monitoring and timely updating of deployed models to guarantee enduring performance and reliability.</li></ul>
Technical Leadership:<ul><li>
Exhibit technical leadership and mentorship to Machine Learning Engineer I, II, and other team members.</li><li>
Encourage knowledge exchange and promote professional growth within the team.</li><li>
Establish and enforce best practices for machine learning system development, including coding standards, code reviews, and comprehensive documentation.</li><li>
Serve as the primary contact for technical inquiries related to machine learning within the team, providing expert guidance and solutions.</li></ul>
Problem-Solving:<ul><li>
Utilize advanced problem-solving skills to navigate and resolve complex technical challenges and obstacles.</li><li>
Foster a collaborative environment for brainstorming and implementing effective solutions with the team and other departments.</li></ul>
Research and Development:<ul><li>
Remain up-to-date with the latest advancements and trends in the fields of software engineering and machine learning.</li><li>
Conduct proactive research to uncover new methods and techniques applicable to future projects.</li><li>
Lead initiatives to explore, test, and implement new technologies and frameworks, ensuring the team is always at the forefront of industry innovations.</li></ul>
Collaboration and Communication:<ul><li>
Engage in effective communication and collaboration across various teams within the organization to ensure alignment and coordination in the execution of machine learning projects.</li><li>
Facilitate transparent and timely communication with all relevant stakeholders, ensuring that all are kept informed of project statuses, challenges, and achievements.</li><li>
Work collaboratively with cross-functional teams, fostering a cooperative environment for the seamless integration of machine learning systems into diverse organizational processes and workflows.</li><li>
Contribute to building strong interdepartmental relationships, enabling the efficient exchange of knowledge and expertise, and ensuring the successful realization of machine learning initiatives.</li></ul>
Additional Responsibilities:<ul><li>
Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies. Tracks and reports progress. Keeps stakeholders apprised of project status and implications for completion.</li><li>
Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication.</li><li>
Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.</li><li>
Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.</li><li>
Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.</li><li>
Works closely with IT on the ongoing improvement of Mount Sinai&rsquo;s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.</li><li>
Demonstrates advanced level proficiency with the principles and methodologies of process improvement. Applies these in the execution of responsibilities in support of a process focused approach.</li><li>
Other duties as assigned.</li></ul> 

Qualifications<ul><li>
Bachelor&rsquo;s degree in Computer Science, Data Science, or a related field.</li><li>
4+ years of relevant experience in machine learning and back-end software development.</li><li>
Demonstrated end-to-end machine learning system development and operation experience, covering the complete Software Development Life Cycle (SDLC).</li><li>
Proficiency in multiple programming languages and machine learning frameworks and tools.</li><li>
Solid experience with both SQL and NoSQL databases.</li><li>
Extensive experience with Big Data technologies like Apache Spark.</li><li>
Hands-on experience in Unix environments.</li><li>
Practical knowledge and experience with at least one cloud system among AWS, Azure, or Google Cloud.</li><li>
Familiarity with continuous development and integration systems such as Jenkins, Git, Azure DevOps, and Terraform.</li><li>
A proven history in developing, deploying, and operating efficient and reliable machine learning systems.</li><li>
Strong leadership and effective communication skills to facilitate cross-functional collaboration throughout the organization.</li><li>
Experience in providing mentorship</li></ul> 
Employer Description
Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai&rsquo;s unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time &mdash; discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients&rsquo; medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News &amp; World Report's Best Hospitals, receiving high &quot;Honor Roll&quot; status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News &amp; World Report&rsquo;s &ldquo;Best Children&rsquo;s Hospitals&rdquo; ranks Mount Sinai Kravis Children's Hospital among the country&rsquo;s best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek&rsquo;s &ldquo;The World&rsquo;s Best Smart Hospitals&rdquo; ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization. 
Compensation
The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $132000 - $198065 Annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.</div>

Machine Learning Engineer III - Generative AI - Windreich Department of Artificial Intelligence & Human Health Research

Apple

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn&rsquo;t have imagined, and now, can&rsquo;t imagine living without. It&rsquo;s the diversity of those people and their ideas that inspires the innovation that runs through everything we do. 
 
Description 
 
APPLE INC has the following available in New York, New York. Work with Product, Design, Project and Engineering to identify, conceptualize and implement the ML use cases for Apple Sports. Prototype ML and Probabilistic algorithms specific to Sports Data. Analyze the Apple Sports Signals and recognize the relevant probabilistic patterns to enhance existing systems while keeping user privacy intact. Execute Statistical tests to identify strength and weakness of ML systems and address by using appropriate ML techniques. Find patterns in the data to enhance the user experience. Document and keep the Apple Sports teams up to date with ML research. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 - $220,900/yr and your base pay will depend on your skills, qualifications, experience, and location. 
 
PAY &amp; BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple&rsquo;s Employee Stock Purchase Plan. You&rsquo;ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 
 
Preferred Qualifications 
 
N/A 
 
Minimum Qualifications 
 
Master&rsquo;s degree or foreign equivalent in Computer Science, Software Engineering, Electrical and Computer Engineering, or related field. 
 
Experience and/or education must include: 
 
Utilizing Python and PyTorch to design, train, and deploy machine learning models for prediction, classification, and generation tasks. 
 
Utilizing modern NLP techniques with Transformer-based architectures including BERT or GPT for text classification and generation. 
 
Applying statistical and probabilistic modeling, including logistic regression, Bayesian inference, and hypothesis testing, to support model development and evaluation. 
 
Designing and executing A/B tests and multivariate experiments to validate machine learning model performance and guide iterative improvements. 
 
Using Scikit-learn, including decision trees, clustering, and ensemble methods to implement classical machine learning algorithms 
 
Utilizing NLTK or similar NLP toolkits for text preprocessing, tokenization, sentiment analysis, and named entity recognition. 
 
Conducting time-series data analysis and pattern recognition using supervised and unsupervised learning techniques. 
 
Using version-controlled scripts and model evaluation frameworks to develop and maintain reproducible machine learning workflows. 
 
Documenting ML research findings and translating experimental results into actionable technical improvements. 
 
Collaborating cross-functionally with engineering, product, and design teams to integrate ML models into user-facing applications. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Machine Learning Engineer

Morgan Stanley

<div>
 Morgan Stanley's Machine Learning Research Department is responsible for working across the Firms many business units and technology teams to solve mission-critical problems. We are a highly motivated and collaborative team of scientists, technologists, and market practitioners.
 
 
 In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities.
 
 
 Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.
 
 
 Interested in joining a team that&rsquo;s eager to create, innovate and make an impact on the world? Read on.
 
 
 We are seeking someone capable of independently tackling research problems that have commercial applications. Ideal candidates will be able to apply the technical expertise and research acumen cultivated in their academic careers to real-world financial and operating problems. Please see our research papers for more: https://www.morganstanley.com/about-us/technology/machine-learning-research-team
 
 
 
 What You&rsquo;ll Bring To The Role
 
 
 
 These candidates will have a track record of exceptionally creative, hands-on, high-impact machine learning research and applications, evidenced by publications in competitive venues. We welcome candidates from both industry and academia, and at various levels of seniority, from Ph.D. students nearing graduation to established researchers. Broad experience across multiple fields is a plus.
 
 
 <ul>
 <li>
 Development experience in Python or R (C, C++, Java, etc is a plus)
 </li>
 <li>
 Deep understanding of statistical learning methods
 </li>
 <li>
 Strong communications and organizational skills
 </li>
 <li>
 4+ years of applicable research experience
 </li>
 <li>
 Bachelor's degree required, Ph.D. desired
 
 
 </li>
 </ul>
 
 What You Can Expect From Morgan Stanley
 
 
 
 We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 85 years. At our foundation are five core values &mdash; putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back &mdash; that guide our more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you&rsquo;ll find trusted colleagues, committed mentors and a culture that values diverse perspectives, individual intellect and cross-collaboration. We Firm is differentiated by the caliber of our diverse team. While our company culture and commitment to inclusion define our legacy and shape our future, helping to strengthen our business and bring value to clients around the world. Learn more about how we put this commitment to action: morganstanley.com/diversity. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry.
 
 
 
 We're committed to bringing passion and customer focus to the business.
 
 
 
 Expected base pay rates for the role will be between $154,000 and $213,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
 
 
 Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.
 
 
 It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.
 
 
 Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).
 
 
</div>

Machine Learning Researcher

James Search Group

<div>
 
 
 AI/ML Engineer
 
 
 
 
 Location:
 
 New York, NY
 
 
 
 Compensation:
 
 $135,000 &ndash; $175,000 base + bonus + full benefits, (401(k), and more)
 
 
 
 Industry:
 
 Global P&amp;C Insurance
 
 
 
 
 
 
 About the role and the company.
 
 
 
 James Search Group is working closely with a top-tier global property &amp; casualty insurance carrier to identify an
 
 AI/ML Engineer
 
 to join their enterprise Data and Artificial Intelligence division. This team is driving innovation across the business by developing and scaling AI capabilities that unlock new value and improve decision-making across underwriting, claims, and customer engagement.
 
 
 
 
 
 As an AI/ML Engineer, you'll collaborate with senior team members to build, refine, and deploy predictive models and intelligent systems. The ideal candidate is skilled in analytics, curious by nature, and passionate about transforming complex data into practical solutions that deliver measurable business impact.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Support the development and deployment of AI/ML models&mdash;including classification, forecasting, uplift and propensity modeling, and foundational model tuning.
 </li>
 <li>
 Collaborate with cross-functional teams to identify use cases where data science can enhance operational efficiency and business performance.
 </li>
 <li>
 Partner with business, IT, and strategy teams to ensure AI models are scalable, impactful, and aligned with organizational goals.
 </li>
 <li>
 Communicate analytical findings clearly to stakeholders with varying levels of technical knowledge.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline; Ph.D. a plus.
 </li>
 <li>
 Minimum of 2 years&rsquo; experience applying advanced analytics methods (e.g., decision trees, logistic regression, neural networks, random forests).
 </li>
 <li>
 Proficiency in R or Python for analytics and model development, including work with both structured and unstructured data.
 </li>
 <li>
 Proven ability to manage and integrate large, complex datasets and an understanding of end-to-end data modeling processes.
 </li>
 <li>
 Strong written and verbal communication skills with the ability to connect technical outputs to business strategy.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Internship or project experience in machine learning, AI engineering, or related roles&mdash;especially in insurance or financial services.
 </li>
 <li>
 Familiarity with actuarial concepts or insurance-specific data models.
 </li>
 <li>
 Enthusiastic about continued learning in AI/ML and staying current with new tools and methodologies.
 </li>
 <li>
 Comfortable in a collaborative, fast-paced, and agile working environment.
 </li>
 </ul>
 
 
 
 
 This is a unique opportunity to grow your career with a highly respected organization investing in next-generation analytics.
 
 
 
 
 
 
 Apply today
 
 to help reshape the future of insurance through data and AI innovation.
 
</div>

<div></div><div><div>Risk Analyst &ndash; Summer Internship</div><div></div><div>
About Gen:</div><div>
Gen is a global company dedicated to powering Digital Freedom through its trusted consumer brands including Norton, Avast, LifeLock, MoneyLion and more. Our combined heritage is rooted in financial empowerment and cyber safety for the first digital generations, and today we deliver award-winning cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users in more than 150 countries.</div><div></div><div>
Together, we share a collective passion and vision to protect consumers and help them grow, manage, and secure their digital and financial lives. We&rsquo;re always looking for smart, fearless and high-impact talent who see AI as a teammate &ndash; leveraging it to move faster and deliver meaningful results.</div><div></div><div>
When you&rsquo;re part of Gen, you&rsquo;ll have the flexibility, tools and support to do your best work and grow your career &ndash; from flexible working options and time off to competitive pay, benefits and well-being programs.</div><div></div><div>
At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation, and continuous learning, and we seek out people with different experiences, identities and ideas to join our team. You&rsquo;ll work with people who back each other, respect each other and understand that our differences are a competitive advantage.</div><div>
If this sounds like you, we&rsquo;d love you to be part of Gen.</div><div></div><div>
About the Role</div><ul><li>
What are you doing this summer? If you&rsquo;re looking for an internship that gives you hands-on experience in a fast-paced, high-impact technology environment&mdash;especially one at the forefront of cybersecurity&mdash;you&rsquo;re in the right place.</li><li>
This is an opportunity to grow your skills, build your resume, and make a real impact.</li></ul><div></div><div>
Key Responsibilities</div><ul><li>
You will oversee, plan and manage an initiative to improve our transaction classification process. This project will have significant impact on important product initiatives, and require programming, analysis and collaboration across multiple teams, and culminate in the launch of the new enhanced process.</li><li>
Develop Machine Learning Models / Rules to Identify specific types of recurring transactions and overall spending trends within bank account data. Examples include:</li><li>
Recurring utility bills</li><li>
Recurring telecom/cellphone bills</li><li>
Other significant recurring trades</li><li>
Spending habits relative to income</li></ul><div></div><div>
About You</div><ul><li>
A current undergraduate or graduate student, rising junior/senior preferred</li><li>
Experience with NLP models</li><li>
Knowledge of AWS/cloud data platforms (Redshift, Snowflake)</li><li>
Previous experience in building models / scores</li><li>
Curious, proactive, and eager to learn in a dynamic, fast paced environment</li><li>
Self-starter who&rsquo;s not afraid to try innovative ideas and learn by doing</li></ul><div></div><div>
Skills:</div><ul><li>
SQL: Intermediate proficiency with complex queries, joins, and window functions</li><li>
Python: Most data modeling will be written in python</li><li>
Ability / willingness to learn how to use various ML/DS packages</li><li>
Data Visualization: Experience with Tableau, Looker, Periscope, or similar tools</li><li>
Excel/Spreadsheets: Advanced skills including pivot tables, VLOOKUP, and basic modeling</li><li>
Statistics: Understanding of basic statistical concepts, A/B testing</li></ul><div></div><div>
Personal Attributes:</div><ul><li>
Visionary leader with a strategic mindset and a passion for leveraging data to drive decision making.</li><li>
Ability to thrive in a fast-paced, high-tech environment and manage complex problem</li></ul><div></div><div>
Internship Details</div><ul><li>
Start Date: June 1</li><li>
Duration: 10 weeks</li><li>
NYC Office</li><li>
Pay Rate: $30.00</li></ul><div></div><div>
Gen is proud to be an equal-opportunity employer, committed to diversity and inclusivity. We base employment decisions on merit, experience, and business needs, without considering race, color, national origin, age, religion, sex, pregnancy, genetic information, disability, medical condition, marital status, sexual orientation, gender identity or expression, military or veteran status, or other unlawful factors. Gen prohibits discrimination based on these protected characteristics and recruits talented candidates from diverse backgrounds.</div><div></div><div> 
We consider individuals with arrest and conviction records and do not discriminate against employees for discussing their own pay or that of other employees or applicants. <div>Learn more about pay transparency</div>.</div><div></div><div> 
To conform to U.S. export control regulations, applicant should be eligible for any required authorizations from the U.S. Government.</div></div>

Intern, Credit Risk Analytics

MedReview Inc.

<div>
 
 
 Position Summary:&nbsp;
 
 
 
 
 
 
 
 
 
 MedReview is looking for a talented and experienced
 
 Data Scientist
 
 to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems. As part of a global team of developers and analysts, the Data Scientist will work with a larger team to design, build, validate, refine, and operationalize models.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 
 Problem Identification:
 
 
 
 
 
 &nbsp;Collaborate with stakeholders to identify business challenges that can be solved through data analysis.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Data Collection &amp; Preparation:
 
 
 
 
 
 &nbsp;Gather data from various sources (SQL databases, APIs, web scraping), then clean and "wrangle" it to ensure accuracy for modeling.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Model Development:
 
 
 
 
 
 &nbsp;Design and implement algorithms and predictive models using machine learning techniques to forecast outcomes or categorize information.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Exploratory Data Analysis (EDA):
 
 
 
 
 
 &nbsp;Analyze datasets to uncover hidden patterns, trends, and anomalies.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Communication &amp; Visualization:
 
 
 
 
 
 &nbsp;Translate technical findings into "data stories" using tools like&nbsp;Tableau&nbsp;or&nbsp;Power BI&nbsp;to influence executive decisions.&nbsp;
 
 
 
 
 
 
 </li>
 </ul>
 
 
 Qualifications:&nbsp;
 
 
 <ul>
 <li>
 
 
 
 
 
 Master&rsquo;s degree or bachelors degree and equivalent experience in a quantitative field (Math, CS, Stats)
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Programming:
 
 
 
 
 
 &nbsp;Proficiency in&nbsp;Python&nbsp;or&nbsp;R&nbsp; along with&nbsp;SQL&nbsp;for database querying.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Mathematics &amp; Statistics:
 
 
 
 
 
 &nbsp;Strong foundation in linear algebra, calculus, and statistical modeling.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 
 Machine Learning:
 
 
 
 
 
 &nbsp;Experience with frameworks like&nbsp;TensorFlow,&nbsp;PyTorch, or&nbsp;scikit-learn.
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 
 Soft Skills:
 
 
 
 
 
 &nbsp;Critical thinking, curiosity, and the ability to explain complex concepts to non-technical audiences.&nbsp;Experience working with global and remote teams
 
 
 
 
 
 
</div>

Data Scientist

Explore 207+ Machine learning intern in New York this March. Find roles across top companies and apply now to boost your career.

207 machine learning intern jobs In New York

2026 PhD Scientist Intern (Delivery Logistics)

Machine Learning Engineer III - Generative AI - Windreich Department of Artificial Intelligence & Human Health Research

Machine Learning Engineer

Machine Learning Researcher

Machine Learning Engineer

Intern, Credit Risk Analytics

Data Scientist