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ai training - research scientist (est)

analyst, data science

machine learning scientist

Mount Sinai Health System

<div>Description
We are looking for a Computational Scientist in Computational Biology and Machine Learning to join our growing translational research program at the Tisch Cancer Institute. Our team studies myeloproliferative neoplasms (MPNs), acute myeloid leukemia (AML), and related myeloid malignancies, combining single-cell multi-omics, clinical data, and artificial intelligence&ndash;based approaches to understand disease mechanisms, identify biomarkers, support drug development, and improve patient care.
The scientist will work closely with longitudinal patient datasets, integrating genomics, immune and cytokine profiling, treatment responses, and clinical trial outcomes.
The scientist will report directly to Dr. Md Babu Mia, lead of the Computational Biology and Machine Learning program within the MPN team.
Responsibilities
Computational Biology &amp; Single-Cell Analytics<ul><li>
Lead analysis of single-cell genomics datasets and build reproducible pipelines for data integration, clustering, differential expression, and clonal architecture reconstruction</li><li>
Apply rigorous statistical methods that appropriately account for sample-level replication, longitudinal structure, and multi-modal data</li></ul> 
Machine Learning &amp; Predictive Modeling<ul><li>
Build machine learning models linking genomic drivers to clinical phenotypes, cytokine profiles, and treatment outcomes using ensemble methods and deep learning</li><li>
Develop interpretable risk stratification models for disease progression and treatment response, with a focus on clinical relevance</li></ul> 
AI &amp; Large Language Model Development<ul><li>
Develop retrieval-augmented generation (RAG) systems and AI-assisted workflows that enable natural-language querying of clinical and genomic datasets</li><li>
Build LLM-powered pipelines for extracting structured information from clinical notes and pathology reports, with an emphasis on transparency and clinical usability</li></ul> 
Data Integration &amp; Infrastructure 
<ul><li>
Build unified data models connecting treatments, laboratory results, cytokines, multi-omic biomarkers, and clinical trial endpoints</li><li>
Maintain HIPAA-compliant databases and ETL pipelines, and develop dashboards and APIs to support cross-institutional collaboration</li></ul> 
Scientific Communication<ul><li>
Prepare publication-ready figures and analyses, and contribute to manuscripts, grant applications, and research proposals</li><li>
Present findings at conferences and collaborate closely with lab scientists and clinicians 
</li></ul>
Qualifications<ul><li>
Masters degree or equivalent in a domain science; Ph.D in Computational Biology, Bioinformatics, Computer Science, Data Science, or related scientific domain preferred.</li><li>
3 years, preferably in a scientific/academic computing environment or equivalent experience.</li><li>
Experience in batch HPC cluster environment with a parallel file system</li><li>
Experience installing and supporting bio and chemistry codes (NAMD, AMBER, Matlab, Gromacs, DESMOND) and laboratory equipment such as sequencers, etc.</li><li>
Experience with MPI, Open MP and numerical libraries</li><li>
Experience with scientific workflows</li><li>
Experience with instrumenting and optimizing application codes</li><li>
Experience in an academic or research community environment</li><li>
Programming experience in any applicable language</li></ul>
Preferred:<ul><li>
Strong experience with next-generation sequencing data analysis, and proficiency in Python and R</li><li>
Demonstrated track record building machine learning models for biomedical applications; familiarity with LLM frameworks or RAG systems</li><li>
Experience with cloud or HPC environments, containerization (Docker), and database design</li><li>
Background in building dashboards, LLM fine-tuning, and working across laboratory, clinical, and computational teams</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 $96461 - $159101.2 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>

Computational Scientist, Computational Biology and Machine Learning - Hematology & Medical Oncology

Lyft

<div>
 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
 
 
 Lyft Ads is one of Lyft&rsquo;s newest and fastest-growing businesses, focused on building the world&rsquo;s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey&mdash;before, during, and after a ride&mdash;by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.
 
 
 We are seeking an
 
 Algorithms Scientist
 
 to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You&rsquo;ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.
 
 
 This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders&mdash;pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
 </li>
 <li>
 Own the end-to-end lifecycle of modeling projects &mdash; including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
 </li>
 <li>
 Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
 </li>
 <li>
 Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
 </li>
 <li>
 Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
 </li>
 <li>
 Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
 </li>
 <li>
 Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
 </li>
 <li>
 Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
 </li>
 <li>
 Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement &mdash; and proactively identifying opportunities to apply them.
 </li>
 <li>
 Contribute to Lyft Ads&rsquo; modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.
 
 
 </li>
 </ul>
 Experience:
 
 
 <ul>
 <li>
 Master&rsquo;s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
 </li>
 <li>
 3&ndash;5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains. Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
 </li>
 <li>
 Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
 </li>
 <li>
 Practical experience building and evaluating:
 </li>
 <ul>
 <li>
 Ranking and relevance models
 </li>
 <li>
 Optimization or pacing algorithms
 </li>
 <li>
 Predictive models for CTR, CVR, or user response
 </li>
 <li>
 Causal or experimentation-based measurement methods
 </li>
 </ul>
 <li>
 Understanding of online/offline evaluation techniques, including:
 </li>
 <ul>
 <li>
 Offline metrics (AUC, NDCG, MRR, calibration)
 </li>
 <li>
 A/B testing methodologies
 </li>
 <li>
 Bias correction and counterfactual estimation
 </li>
 </ul>
 <li>
 Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
 </li>
 <li>
 Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
 </li>
 <li>
 Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
 </li>
 <li>
 Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.
 
 
 </li>
 </ul>
 
 Benefits:
 
 
 
 <ul>
 <li>
 Great medical, dental, and vision insurance options with additional programs available when enrolled
 </li>
 <li>
 Mental health benefits
 </li>
 <li>
 Family building benefits
 </li>
 <li>
 Child care and pet benefits
 </li>
 <li>
 401(k) plan to help save for your future
 </li>
 <li>
 In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
 </li>
 <li>
 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
 </li>
 <li>
 Subsidized commuter benefits
 </li>
 <li>
 Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
 
 
 </li>
 </ul>
 Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
 
 
 Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule &mdash; Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
 
 
 The expected base pay range for this position in the New York City area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
 
 
 Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
</div>

Data Scientist, Algorithms - Lyft Ads

JPMorganChase

<div>JOB DESCRIPTION 
As part of the Commercial &amp; Investment Bank, J.P. Morgan Payments enables organizations of all sizes to execute transactions efficiently and securely, transforming the movement of information, money and assets. We tackle complex challenges at every stage of the payment lifecycle and our industry-leading solutions facilitate seamless transactions across borders, industries and platforms. Operating in over 160 countries and handling more than 120 currencies, we are the largest processor of USD payments, with a daily transaction volume of $10 trillion.
As a Associate Applied AI/ML Scientist within our Payment Solutions team, you will be instrumental in utilizing artificial intelligence and machine learning technologies to augment our payment solutions and stimulate business expansion. Your role will involve researching, experimenting, developing, and transitioning high-quality machine learning models, services, and platforms into production to streamline payment processes, bolster fraud detection, and enrich customer experience. You will also be tasked with designing and executing highly scalable and dependable data processing pipelines, conducting analysis, and deriving insights to boost and optimize business outcomes. Working in collaboration with cross-functional teams, you will identify opportunities for AI/ML applications within the payments ecosystem.
Job Responsibilities:<ul><li>
Actively collaborate with Product, Technology, and other cross-functional teams to gain a deep understanding of complex business problems and formulate data-driven solutions to address these challenges in key areas of the payments&rsquo; domain.</li><li>
Design, develop, and deploy machine learning and AI solutions that meet success metrics aligned with business goals, while considering constraints such as model complexity, scalability, and latency.</li><li>
Partner with Risk and Compliance teams to ensure comprehensive model documentation, track performance metrics, and maintain adherence to regulatory compliance standards.</li><li>
Translate model outcomes into business impact metrics and communicate complex concepts to senior management and stakeholders.</li></ul>
Required qualifications, capabilities, and skills:<ul><li>
Bachelor's degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research) with a minimum of 3 years of industry experience. Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services is required.</li><li>
Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Experience with Jupyter Notebook/Lab is essential.</li><li>
3+ years of extensive experience in Natural Language Processing (NLP) or Large Language Models (LLM),or Computer Vision and other machine learning techniques, including classification, regression algorithms.</li><li>
Solid Understanding of algorithms in machine learning, AI, and neural network, including Large Language Models (LLM) and Generative AI as well as familiarity with state-of-the-art practices and advancements in these domains.</li><li>
Proficient in both basic and advanced exploratory data analysis (EDA), with an understanding of the limitations and implications of different methodologies.</li><li>
Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans. You possess strong cognitive and communication skills, characterized by clear and articulate expression. You excel at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes.</li></ul>
Preferred Qualifications, capabilities and skills<ul><li>
Experience in the financial services industry, particularly within investment banking operations.</li><li>
Cloud computing: Amazon Web Service, Azure, Docker, Kubernetes, DataBricks, Snowflakes.</li></ul>
ABOUT US 
<div>
<div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
<div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
</div></div></div> 
 
ABOUT THE TEAM 
 
J.P. Morgan&rsquo;s Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Applied AI/ML Associate

Data Scientist, Analytics (Technical Leadership)

Andiamo

<div>
 Data Scientist
 
 
 
 About The Role
 
 
 
 When you work in this role, you&rsquo;ll tackle tough problems alongside other scientists and engineers&mdash;people who will challenge your ideas, share knowledge, and collaborate on impactful projects. You&rsquo;ll be doing work that matters, developing solutions to complex real-world problems using data, invention, and rigorous inquiry.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Independently research and develop hypotheses based on diverse real-world datasets.
 </li>
 <li>
 Conduct literature reviews to apply cutting-edge methodologies for extracting meaningful signals from data.
 </li>
 <li>
 Partner with engineers and stakeholders to rigorously explore and test your theories.
 </li>
 <li>
 Stay engaged in the academic community by joining reading circles and attending seminars to keep up with the latest research.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 1&ndash;5+ years of experience in applied data analysis and prediction, preferably in an industry setting.
 </li>
 <li>
 Degree in a technical or quantitative discipline such as statistics, mathematics, physics, electrical engineering, or computer science.
 </li>
 <li>
 Proficiency in Python and SQL.
 </li>
 <li>
 Experience conducting in-depth research projects involving real-world data.
 </li>
 <li>
 Ability to think independently, approach analysis creatively, and communicate complex ideas clearly.
 </li>
 <li>
 Background in finance is not required&mdash;strong research skills are most important.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life and disability insurance.
 </li>
 <li>
 Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms.
 </li>
 <li>
 Learning: Tuition reimbursement, conference and training sponsorship.
 </li>
 <li>
 Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves.
 </li>
 <li>
 Hybrid Work Policy: Flexible in-office days with budget for home office setup.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 The base pay for this role will be between
 
 $165,000 and $300,000
 
 . This role may also be eligible for additional forms of compensation and benefits such as discretionary bonuses, health and wellness plans, and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation will depend on skills, qualifications, and experience.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist - Data-Driven Global Investment Firm

Crosby

<div>
 
 About Crosby AI
 
 
 
 Crosby is an AI-first legal platform reimagining corporate legal services from the ground up. We are a team of technologists and legal experts who build proprietary technology and human-in-the-loop workflows that meaningfully improve how lawyers and machines work together &mdash; delivering speed, consistency, and quality across high-stakes work.
 
 
 Our systems review complex documents faster and with exceptional accuracy, combining advanced AI with structured legal expertise. Clients receive AI-powered redlines, commentary, and negotiation guidance within hours, at a predictable, volume-based price.
 
 
 Backed by Sequoia, Index Ventures, and Bain Capital Ventures, we're building the end-to-end contracting platform for the next generation of fast-growing companies.
 
 
 
 The Team
 
 
 
 The Engineering team builds the core systems and infrastructure that power Crosby&rsquo;s AI-first legal platform. We work at the intersection of machine learning, product, and legal expertise to deliver intelligent, reliable systems that operate in high-stakes environments.
 
 
 We prioritize speed, ownership, and high standards &mdash; shipping quickly while maintaining rigor in everything we build.
 
 
 
 The Role
 
 
 
 As a Data Scientist at Crosby, you'll play a critical role in developing the models and data systems that power our AI-driven legal platform. You&rsquo;ll work across the full lifecycle &mdash; from data definition and labeling strategy to model development, evaluation, and iteration in production.
 
 
 You&rsquo;ll partner closely with engineers, product teams, and legal experts to translate complex legal workflows into structured machine learning systems. Beyond modeling, you&rsquo;ll help ensure our systems are accurate, reliable, and continuously improving in real-world use.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop evaluation systems: Build metrics, benchmarks, and experimentation frameworks to measure and improve model performance.
 </li>
 <li>
 Drive data strategy: Partner with legal and product teams to define labeling schemas, curate high-quality datasets, and improve data pipelines.
 </li>
 <li>
 Support production systems: Work closely with engineering to deploy models, monitor performance, and iterate based on real-world usage.
 </li>
 <li>
 Apply AI pragmatically: Leverage LLMs and other modern techniques to solve product problems, balancing sophistication with reliability and speed.
 </li>
 <li>
 Collaborate cross-functionally: Partner with engineering, product, and legal teams to deliver end-to-end systems that improve customer outcomes.
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 1&ndash;5 years of experience in data science, machine learning, or applied NLP, ideally in a fast-paced startup environment
 </li>
 <li>
 Strong foundation in machine learning, statistics, and data analysis, with proficiency in Python
 </li>
 <li>
 Hands-on experience working with LLMs, NLP systems, or unstructured text data
 </li>
 <li>
 Experience working across the full ML lifecycle &mdash; from data curation and experimentation to deployment and monitoring
 </li>
 <li>
 Highly analytical with strong problem-solving skills and the ability to translate ambiguous problems into structured solutions
 </li>
 <li>
 Strong communicator who can collaborate effectively with both technical and non-technical stakeholders
 
 
 </li>
 </ul>
 
 Equal Opportunity
 
 
 
 Crosby is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the New York City Fair Chance Act.
 
 
 Pursuant to New York Labor Law Section 194-b, the US Pay Range for this position is listed below. Final compensation will be determined based on skills, experience, and qualifications.
 
 
 
 Compensation Range: $200k&ndash;$250k
 
 
 
 Compensation Range: $200K - $250K
 
 
</div>

Data Scientist

<div>Description
We are seeking a highly motivated Staff Scientist to lead and support the analysis of large-scale molecular datasets in a dynamic, collaborative research environment. This role focuses on cutting-edge functional genomics, with an emphasis on single-cell and multi-omic technologies. 
The Staff Scientist will drive computational analysis of high-dimensional datasets, partnering closely with a well-integrated computational-experimental team to generate biological insights from complex genomic data. The ideal candidate has deep expertise in single-cell transcriptomics and epigenomics, experience handling large-scale datasets, and strong quantitative and programming skills. Experience in machine learning and AI approaches is highly desirable. 
Responsibilities<ul><li>
Lead analysis of single-cell RNA-seq and multiome datasets (joint RNA/ATAC profiling)</li><li>
Perform integrative analysis across modalities, including bulk RNA-seq, ATAC-seq, and DNA methylation datasets</li><li>
Develop processing pipelines for novel single cell multiomic technologies</li><li>
Apply statistical modeling and machine learning methods to identify cellular states, regulatory programs, and epigenetic signatures</li><li>
Design and implement integrative multi-omic analyses across cohorts and experimental systems</li><li>
Present findings internally and contribute to publications and grant applications</li><li>
Stay current with emerging single-cell and AI-driven genomic analysis methodologies</li></ul> 

Qualifications<ul><li>
Ph.D. in Biological Science or related field</li><li>
Three years experience</li></ul> 
Preferred Skills<ul><li>
PhD in Computational Biology, Bioinformatics, Genomics, Statistics, Computer Science, or related field (or equivalent experience)</li><li>
Strong experience analyzing bulk and single-cell RNA-seq and epigenomic data</li><li>
Proficiency in R, including common single-cell analysis frameworks</li><li>
Experience working with large-scale genomic datasets and high-performance computing environments</li><li>
Strong statistical background and data visualization skills</li><li>
Experience analyzing DNA methylation data (e.g., array-based or sequencing-based approaches)</li><li>
Experience analyzing long-read RNA sequencing datasets</li><li>
Demonstrated use of machine learning/AI methods for genomic data integration or prediction</li><li>
Familiarity with cloud-based workflows and reproducible pipeline development</li><li>
Track record of publications in peer-reviewed journals</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 $58661 - $98978.78 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>

Associate Scientist (Computational Genomics & Large-Scale Molecular Data Analysis) - Neurology

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