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machine learning intern

Software Engineer, Machine Learning

Spotify

<div><div><div><div><div><div>Engineering</div></div></div><div><div>
Machine Learning</div></div></div><div><div>
Permanent</div></div><div><div>
New York</div></div><div><div>
The Personalization team at Spotify aims to make content discovery effortless and enjoyable for every listener. By deeply understanding music, podcasts, audiobooks, and videos, we deliver exceptional recommendations that keep millions of people worldwide engaged with our products daily. Our work spans experiences like Home, Search, curated playlists such as Discover Weekly and Daylist, and cutting-edge innovations including AI DJ and AI Playlists.</div></div><div><div><div><br>
</div><div>Home plays a pivotal role in shaping the technical vision and architecture of recommendation systems that power the Spotify Home page. You&rsquo;ll work on foundational components that enable the larger Home experience, user activation, listening habits across content types, and expanding its technology to take advantage of LLMs and other Generative Recommender products. As a Staff Machine Learning Engineer in Home, you&rsquo;ll focus on recommender systems modeling at the intersection of generative recommenders and a foundational understanding of user taste across music and talk content.
</div><div></div><br>
<div>You will define and execute the ML technical strategy for Home, building the next generation of Spotify&rsquo;s recommendation systems, user representations, and supporting technical architecture. Join us and you&rsquo;ll help millions of users discover and connect with the world&rsquo;s audio content every day.</div></div></div></div><div><div><p>
What You'll Do</p><ul><li>
Define and drive the ML technical strategy for Home, focusing on generative recommendation approaches</li><li>
Build models that improve user representations, personalization, and relevance across Spotify&rsquo;s experiences</li><li>
Collaborate with a cross-functional agile team spanning user research, design, data science, product management, and engineering</li><li>
Prototype and productionize new modeling approaches at scale, serving hundreds of millions of users worldwide</li><li>
Lead high-impact projects from ideation through deployment, setting best practices for ML development, testing, evaluation, and experimentation</li><li>
Partner with tech leaders and stakeholders to influence priorities and ensure long-term scalability and impact</li><li>
Stay engaged with the broader ML and Search research community, applying emerging trends to Spotify&rsquo;s challenges</li></ul></div></div><div><div><p>
Who You Are</p><ul><li>
You have a strong background in machine learning and recommender systems, bridging research and user impact</li><li>
You have hands-on experience training and operating transformer models in production, or strong interest in doing so</li><li>
You have production experience developing large-scale ML systems in Java, Scala, Python, or similar languages. Experience with PyTorch or TensorFlow is a strong plus</li><li>
You are comfortable navigating ambiguity and leading high-impact projects from start to finish</li><li>
You&rsquo;re a systems thinker and strong communicator who can align and influence technical and product stakeholders</li><li>
You care deeply about agile processes, data-driven development, and reliability.You&rsquo;re eager to apply emerging ML trends, particularly in LLMs and generative recommenders, to Spotify&rsquo;s challenges</li></ul></div></div><div><div><p>
Where You'll Be</p><ul><li>
We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.</li><li>
This team operates within the Eastern Standard time zone for collaboration.</li></ul></div></div><div><div><p>
Learn about life at Spotify</p></div><div><div>
The United States base range for this position is $215,136- $307,337 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.</div></div></div><div><div><p>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Staff Machine Learning Engineer

Point72

<div><div><div><p><b>EXPERIENCE</b></p>
<div>Early Career</div>
</div><div><p><b>LOCATION</b></p>
<div>New York</div>
</div><div><p><b>FOCUS</b></p>
<div>Data Science &amp; Analytics | Systematic Data</div>
</div><div><p><b>BUSINESS</b></p>
<div>Cubist</div></div></div></div>
<br><div><h3 class="jobSectionHeader"><b>About Cubist</b></h3>
<p>
Cubist Systematic Strategies is one of the world&rsquo;s premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.</p><h3 class="jobSectionHeader"><b><br>
Role</b></h3>
<p>
We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance.</p><p></p><p><br>
Cubist&rsquo;s data services group is looking for a Data Scientist Intern to join our dedicated team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.</p><p></p><p><br>
This exceptional individual will be a member of a small team of Data Scientists/Analysts who play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments.</p><h3 class="jobSectionHeader"><b><br>
Responsibilities</b></h3>
<ul><li>Analyzing financial datasets and preparing reports for investment teams</li><li>
Creating derived data content and data ingestion pipelines</li><li>
Identifying potential data sources</li><li>
Engaging with vendors to understand characteristics of datasets</li><li>
Defining and automating qualitative data checks</li><li>
Assisting with data questions and requests from investment teams</li><li>
Creating and maintaining internal documentation on datasets</li></ul><br>
<h3 class="jobSectionHeader"><b>
Requirements</b></h3>
<ul><li>Basic level programming experience in Python and SQL</li><li>
Financial industry experience preferred but not required</li><li>
Strong organization, communication, and interpersonal skills</li><li>
Attention to detail and a love of process</li><li>
Strong oral and written communication skills</li><li>
Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues</li><li>
Ability to multitask and prioritize assignments</li><li>
Commitment to the highest ethical standards</li></ul><p></p><p><br>
The annual base salary range for this role is $125,000-$130,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.</p></div>

Data Scientist Intern

<div><div><div><div><div><div>Engineering</div></div></div><div><div>
Machine Learning</div></div></div><div><div>
Permanent</div></div><div><div>
New York</div></div><div><div>
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Discover Weekly to AI DJ, we&rsquo;re behind some of Spotify&rsquo;s most-loved features. We built them by understanding the world of music, podcasts, and listeners better than anyone else. Join us and you&rsquo;ll keep millions of users listening by making great recommendations to each and every one of them.</div></div><div><div><div><br>
</div><div>The Next Generation Sessions (NextGen) product area within Personalization is evolving listening beyond playlists, inventing new personalized listening (and watching!) sessions such as AI DJ, AI Playlist, Blend, Podcast Discovery Feed, and Music Discovery Feed. NextGen is a team of about 100 engineers, scientists, product managers, and music and voice domain experts working remotely and in offices in New York, Boston, London, and Stockholm.</div><div><br>
</div><div>This ML Engineering Manager role will provide technical leadership to a newly formed squad of ~12 engineers focusing on exciting new AI-driven music session experiences. In collaboration with a cross-functional and cross-team leadership group, you will drive expansion of NextGen's AI experiences in music, leveraging the success of AI DJ and AI Playlist, advancing and spearheading the development of entirely new music recommendations experiences and capabilities.</div></div></div></div><div><div><p>
What You'll Do</p><ul><li>
Lead a talented team of ML, backend, and data engineers to build and launch innovative AI-driven personalized music experiences</li><li>
Debate and align technical strategies with senior engineering leaders and partner teams, translate these strategies clearly back to your squad, and actively guide architectural vision and day-to-day ML modeling and coding decisions</li><li>
Bring external experience in generative AI and agent frameworks to enhance Spotify's personalized music sessions</li><li>
Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross-functional teams</li><li>
Champion AI-assisted coding practices, continually expanding the team's technical capabilities</li><li>
Foster strong research partnerships to scale innovative solutions from experimentation to production</li><li>
Develop and grow your team's talent through hiring, coaching, mentoring, and fostering a collaborative, adaptive culture</li></ul></div></div><div><div><p>
Who You Are</p><ul><li>
Experienced leading delivery of consumer-facing ML products at scale</li><li>
Energized by rapid change, ambiguity, and opportunity, with a proven track record transforming innovative ideas into impactful products</li><li>
Skilled with current generative AI and agent technologies</li><li>
Actively using AI-assisted coding and product development tools to prototype new products</li><li>
Expert in modern ML theory, practices, and their practical implementation</li><li>
Comfortable providing detailed technical direction and resolving complex engineering challenges</li><li>
Collaborative and influential, thriving in strategic discussions with senior engineers and managers</li><li>
Focused on user outcomes, rigorously grounding decisions in user data and insights</li><li>
Experienced in nurturing technical talent, committed to growing engineers' skills in technology and leadership</li></ul></div></div><div><div><p>
Where You'll Be</p><ul><li>
We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location. The squad is based in New York City.</li><li>
This team operates within the Eastern Standard time zone for collaboration.</li></ul></div></div><div><div><p>
Learn about life at Spotify</p></div><div><div>
The United States base range for this position is $176,166- $251,666 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.</div><div></div><div><br>
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what&rsquo;s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It&rsquo;s in our differences that we will find the power to keep revolutionizing the way the world listens.</div><div></div><div><br>
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we&rsquo;re here to support you in any way we can.</div><div></div><div><br>
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world&rsquo;s most popular audio streaming subscription service.</div></div></div><div><div><p>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Machine Learning Engineering Manager, Personalization

NoGood

<div><p>Ready to join one of the fastest-growing (and coolest!) marketing agencies in the country? You've arrived at the right place!</p><h3 class="jobSectionHeader"><b>
We are:</b></h3><p>
A team of proven growth experts, creatives, and data scientists who help unlock rapid growth for some of the world&rsquo;s most iconic brands. We&rsquo;ve successfully grown many companies from hundreds to millions in revenue. We have worked with VC-backed startups and Fortune 500 brands including TikTok, Oura, Nike, P&amp;G, Intuit, and many more. We are based out of New York City and support startups and scale-ups around the globe.</p><h3 class="jobSectionHeader"><b>
The role:</b></h3><p>
NoGood is looking for a hands-on AI Search and Content Intern to help drive implementation and organic traffic growth. You will assist in day-to-day keyword research, content planning, writing, SEO/AEO optimizations and more! As a team member, you will learn from SEO, AEO, and organic traffic growth experts. This position can be remote, but preferably will be based out of our headquarters in New York City.</p><h3 class="jobSectionHeader"><b>
You&rsquo;ll do:</b></h3><ul>
<li>Support content strategy for NoGood as a client by authoring thought leadership pieces and blog posts that drive traffic.</li>
<li>Produce winning content in the form of blog and landing page content.</li>
<li>Support optimizing existing marketing assets to provide a better customer journey in our marketing funnels.</li>
<li>Partner with the marketing team to work on new initiatives to drive growth.</li>
<li>Conduct market research to track industry trends and competitive analysis to inform organic marketing strategies.</li>
<li>Oversee and learn technical implementation methods for improving organic visibility.</li>
<li>Research emerging AI search trends (Google SGE, Perplexity, ChatGPT Browse, Bing Copilot, etc.)</li>
<li>Analyze how AI models summarize and cite web content, and identify optimization opportunities.</li>
<li>Support creation of AEO briefs with a focus on content frameworks for LLMs.</li>
<li>Use tools like Goodie, Ahrefs, Search Console, Perplexity, and ChatGPT to monitor shifts in visibility.</li>
<li>Collaborate with the content team to draft and test AEO-optimized articles and metadata.</li>
<li>Other responsibilities as assigned.</li>
</ul><p><b>
Requirements</b></p><h3 class="jobSectionHeader"><b>
You have:</b></h3><ul>
<li>Strong career interest in marketing, content, marketing analytics, and AI Search (AEO).</li>
<li>Proficiency in SEMRush, Ahrefs, Google Search Console, Google Analytics is a plus.</li>
<li>Excellent project management skills &ndash; able to juggle multiple priorities and meet deadlines.</li>
<li>A can-do attitude and able to complete tasks with little supervision.</li>
<li>Excellent writing skills to be able to craft thought leadership pieces (long-form) and persuasive, snappy copy (short-form).</li>
<li>Excellent communication and interpersonal skills.</li>
<li>Working knowledge of Wordpress is a must. Ability to build articles within CMS and implementation of optimization efforts.</li>
<li>Experience (or a strong understanding) using marketing automation software like HubSpot is a plus.</li>
<li>Current enrollment in either a 4-year program or Graduate program at an accredited school.</li>
</ul><p><b>
Benefits</b></p><p><b>
Perks Of Becoming a NoGoodie:</b></p><ul>
<li>
Flex Work Environment: hybrid at HQ and remote globally</li>
<li>Level Up: Mentorship &amp; Career Growth Support</li>
<li>Always Be Learning: Access to Top-tier Resources &amp; Industry Experts</li>
<li>Work Hard, Play Harder: Quarterly Team Trips (Onsite and Offsite)</li>
<li>Fuel Your Day: Free Lunch, Snacks, Cold Brew, &amp; Happy Hours</li>
<li>Grow With Us: Endless Opportunities to Lead &amp; Succeed</li>
Keep on Shining: Ongoing Employee Development Programs<br>
<li>
</li>
</ul><p><b>EEO &amp; Compensation Transparency Statement:</b></p><p>
NoGood is committed to pay transparency and equity among all employees and provides employees an environment where pay transparency and dialogue on compensation are allowed. NoGood complies with federal, state, and local laws on compensation, pay transparency, and pay equity. We take factors including geographic location, education, training, skillset, market rates, certifications, and more into consideration when constructing pay ranges for new and existing roles within our organization. The compensation range for this position is $16.50-$20/hour</p><p>
At NoGood, we understand that diversity in the workplace is vital to a company&rsquo;s success and growth. We strive to make sure that our team members are included and have a sense of belonging that makes us a great company to work with and a great company to work for. To that end, NoGood is committed to Equal Opportunity Employment and complies with all Equal Opportunity Employment laws. We will consider all qualified applicants without regard to race, religion, color, national origin, sex, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will work to make reasonable accommodations available in the job application and interview process, to perform essential duties of the job function, and to retrieve other benefits and privileges of employment with our organization.</p></div><p></p>

AI Search & Content Intern

Intuit

<div><h2 class="jobSectionHeader"><b>Overview</b></h2><p>
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.</p><p>
Intuit&rsquo;s Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. TurboTax simplifies tax preparation and enables our customers to file with confidence. By harnessing the power of data and artificial intelligence (AI), we continuously innovate and evolve our consumer offerings to deliver even greater value.</p><div>
As we expand into Consumer Lending within the Consumer Group, Intuit Credit Karma is looking for an innovative, experienced, and hands-on Staff AI Scientist to join our Consumer Risk AI Science team. In this role, you&rsquo;ll develop cutting-edge credit risk AI/ML models for new lending products. Join a collaborative and inventive team of AI scientists and machine learning engineers where your work will have a direct impact on hundreds of thousands of customers.</div><p><b><br>
Responsibilities</b></p><h3 class="jobSectionHeader">
What you&rsquo;ll do:</h3><ul><li>
Contribute to the credit risk AI science initiatives for the new and evolving Money product offerings focusing on the lending domain, including complete hands-on ownership of the model lifecycle, sharing ownership of success and key results at the program-level, and driving the data strategy across all involved teams.<ul><li>
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for various short-term lending products (e.g., tax refund advances, BNPL, installment loans, single payment loans, and early wage access)</li><li>
Collaborate with credit policy, product and fraud risk teams to ensure models align with business goals and product offering to drive actionable lending decisions</li><li>
Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and both commercially available and proprietary Machine Learning and AI infrastructures</li><li>
Deploy models in a production environment in collaboration with other AI scientists and machine learning enginers</li><li>
Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other relevant regulatory frameworks</li></ul></li><li>
Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.</li><li>
Research and implement practical and creative machine learning and statistical approaches suitable for our fast-paced, growing environment.</li></ul><h3 class="jobSectionHeader">
What&rsquo;s great about the role:</h3><ul><li>
Solve hard, meaningful problems giving customers access to their hard-earned money alongside fun, smart people.</li><li>
Experience professional growth and encourage growth throughout the team.</li><li>
Work cross functionally (with executives, engineering, policy &amp; rules, product, analytics, operations and other AI science teams) to ensure efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact</li></ul><p><b><br>
Qualifications</b></p><h3 class="jobSectionHeader">
Minimum Qualifications:</h3><ul><li>
Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline</li><li>
7-10 years of work experience in AI Science / Machine Learning and related areas</li><li>
Authoritative knowledge of Python and SQL</li><li>
Relevant work experience in fintech credit risk, with deep understanding of payment systems, money movement products, banking, and lending</li></ul><ul><li>
Experience leveraging credit bureau, tax and cash flow data in credit risk model development</li><li>
Experience with and deep understanding of developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning, tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.</li><li>
Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation</li><li>
Ability to quickly develop a deep statistical understanding of large, complex datasets</li><li>
Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models</li><li>
Strong business problem solving, communication and collaboration skills</li><li>
Ambitious, results oriented, hardworking, team player, innovator and creative thinker</li><li>
Proven experience defining and driving end-to-end modeling frameworks, methodologies, or best practices across multiple product teams or domains.</li><li>
Demonstrated ability to evaluate and integrate emerging AI/ML technologies, contributing to the company&rsquo;s external technical visibility and innovation agenda.</li></ul><h3 class="jobSectionHeader">
Preferred Qualifications:</h3><ul><li>
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.</li><li>
Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow</li><li>
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring, and version control</li><li>
Experience with experimentation design and analysis, including A/B testing and statistical analysis.</li></ul><p><br>
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:</p><p></p><div><i><br>
Bay Area: $205,500 - $278,000</i></div><div><i>
Southern California: $191,500.00 - $259,000.00</i></div><div><i>
New York: $201,500.00 - $273,000.00.</i></div></div><p></p>

Staff Credit Risk AI Scientist - Fintech Consumer Risk

<div><h2 class="jobSectionHeader"><b>Overview</b></h2><p>
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.</p><p>
Intuit&rsquo;s Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. TurboTax simplifies tax preparation and enables our customers to file with confidence. By harnessing the power of data and artificial intelligence (AI), we continuously innovate and evolve our consumer offerings to deliver even greater value.</p><div>
As we expand into Consumer Lending within the Consumer Group, Intuit Credit Karma is looking for an innovative, experienced, and hands-on Senior AI Scientist to join our Consumer Risk AI Science team. In this role, you&rsquo;ll develop cutting-edge credit risk AI/ML models for new lending products. Join a collaborative and inventive team of AI scientists and machine learning engineers where your work will have a direct impact on hundreds of thousands of customers.</div><p><b><br>
Responsibilities</b></p><h3 class="jobSectionHeader">
What you&rsquo;ll do:</h3><ul><li>
Contribute to the credit risk AI science initiatives for the new and evolving Money product offerings focusing on the lending domain, including complete hands-on ownership of the model lifecycle, sharing ownership of success and key results at the program-level, and driving the data strategy across all involved teams.<ul><li>
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for various short-term lending products (e.g., tax refund advances, BNPL, installment loans, single payment loans, and early wage access)</li><li>
Collaborate with credit policy, product and fraud risk teams to ensure models align with business goals and product offering to drive actionable lending decisions</li><li>
Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and both commercially available and proprietary Machine Learning and AI infrastructures</li><li>
Deploy models in a production environment in collaboration with other AI scientists and machine learning enginers</li><li>
Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other relevant regulatory frameworks</li></ul></li><li>
Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.</li><li>
Research and implement practical and creative machine learning and statistical approaches suitable for our fast-paced, growing environment.</li></ul><h3 class="jobSectionHeader">
What&rsquo;s great about the role:</h3><ul><li>
Solve hard, meaningful problems giving customers access to their hard-earned money alongside fun, smart people.</li><li>
Experience professional growth and encourage growth throughout the team.</li><li>
Work cross functionally (with executives, engineering, policy &amp; rules, product, analytics, operations and other AI science teams) to ensure efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact</li></ul><div></div><p><b><br>
Qualifications</b></p><h3 class="jobSectionHeader">
Minimum Qualifications:</h3><ul><li>
Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline</li><li>
3-6 years of work experience in AI Science / Machine Learning and related areas</li><li>
Authoritative knowledge of Python and SQL</li><li>
Relevant work experience in fintech credit risk, with deep understanding of payment systems, money movement products, banking, and lending</li><li>
Experience leveraging credit bureau, tax and cash flow data in credit risk model development</li><li>
Experience with and deep understanding of developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning, tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.</li><li>
Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation</li><li>
Ability to quickly develop a deep statistical understanding of large, complex datasets</li><li>
Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models</li><li>
Strong business problem solving, communication and collaboration skills</li><li>
Ambitious, results oriented, hardworking, team player, innovator and creative thinker</li></ul><h3 class="jobSectionHeader">
Preferred Qualifications:</h3><ul><li>
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.</li><li>
Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow</li><li>
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring, and version control</li><li>
Experience with experimentation design and analysis, including A/B testing and statistical analysis.</li></ul><p><br>
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:</p><p></p><div><i><br>
Bay Area California: 173,500 - 234,500</i><br>
<i>Southern California: 160,500 - 217,000</i><br>
<i>New York, NY: 172,000 - 232,500</i></div></div>

Senior Credit Risk AI Scientist - Fintech Consumer Risk

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