associate researcher i-pathology molecular and cell based medicine

associate researcher i-pathology, molecular and cell based medicine

associate researcher ii - genetics (sebra lab)

academic researcher - fully remote | upto $110/yr

administrative assistant ii - institute for translational epidemiology - ism

associate researcher i-pathology molecular and cell based medicine Jobs in New York

associate researcher i-pathology, molecular and cell based medicine Jobs in New York

associate researcher ii - genetics (sebra lab) Jobs in New York

academic researcher - fully remote | upto $110/yr Jobs in New York

administrative assistant ii - institute for translational epidemiology - ism Jobs in New York

ai training research scientist est

Verition Fund Management LLC

<div>
 Verition Fund Management LLC (&ldquo;Verition&rdquo;) is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility &amp; Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short &amp; Capital Markets Trading, and Global Quantitative Trading.
 <br/>
 <br/>
 We are seeking a highly motivated and technically strong Data Scientist to join the centralized Long/Short Equity team at a leading multi-strategy hedge fund. This team partners directly with portfolio managers and analysts across the L/S Equity business to identify, evaluate, and deploy data-driven insights that enhance investment decision-making and alpha generation.
 <br/>
 <br/>
 The ideal candidate will combine strong technical and analytical capabilities with a practical understanding of financial markets. This role will focus on sourcing, analyzing, and operationalizing alternative and traditional datasets, building research tools, and developing scalable analytical frameworks that support discretionary equity investing.
 <br/>
 <br/>
 <strong>
  Key Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Analyze large structured and unstructured datasets to identify predictive signals and investment insights for L/S Equity portfolio managers.
  </li>
  <li>
   Source, evaluate, and onboard alternative datasets relevant to equity investing, including consumer, transactional, web, geolocation, sentiment, and fundamental datasets.
  </li>
  <li>
   Work closely with portfolio managers, analysts, and sector teams to understand investment processes and develop tailored data-driven solutions.
  </li>
  <li>
   Apply statistical techniques and machine learning methods where appropriate to improve signal generation, company analysis, and portfolio insights.
  </li>
  <li>
   Create dashboards, visualizations, and reporting tools that enable PMs and analysts to consume data effectively and make faster investment decisions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   2+ years of experience in data science, quantitative research, or data analytics within a hedge fund, asset manager, investment bank, or technology-focused environment.
  </li>
  <li>
   Strong proficiency in Python, including experience with libraries such as pandas, NumPy, scikit-learn, and related data science tools.
  </li>
  <li>
   Experience working with large datasets, SQL databases, APIs, and modern data processing frameworks.
  </li>
  <li>
   Understanding of equity markets and investment workflows, ideally within a long/short equity investing environment a plus but not required
  </li>
  <li>
   Strong problem-solving and critical thinking abilities with a demonstrated ability to derive actionable insights from complex datasets.
  </li>
  <li>
   Ability to communicate findings clearly to both technical and non-technical stakeholders, including portfolio managers and investment analysts.
  </li>
  <li>
   Exposure to generative AI tooling for investment research workflows.
  </li>
  <li>
   Knowledge of software engineering best practices, including version control and CI/CD workflows.
  </li>
 </ul>
</div>


L/S Equity - Sector Data Science

Fusemachines

<div>
 <strong>
  About Fusemachines
  <br/>
  <br/>
 </strong>
 Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 <br/>
 <br/>
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 <br/>
 <br/>
 <strong>
  Type: Full-time, Remote
  <br/>
  <br/>
 </strong>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We&rsquo;re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You&rsquo;ll work across the ML lifecycle&mdash;from problem framing and data exploration to model development, evaluation, deployment, and monitoring&mdash;often in partnership with client stakeholders and internal delivery teams.
 <br/>
 <br/>
 You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Problem Framing &amp; Stakeholder Partnership
  </li>
  <ul>
   <li>
    Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)
   </li>
   <li>
    Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)
   </li>
  </ul>
  <li>
   Data Analysis &amp; Feature Engineering
  </li>
  <ul>
   <li>
    Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses
   </li>
   <li>
    Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices
   </li>
   <li>
    Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions
   </li>
  </ul>
  <li>
   Model Development (Core ML)
  </li>
  <ul>
   <li>
    Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)
   </li>
   <li>
    Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation
   </li>
   <li>
    Build time series models (statistical and ML/DL approaches) and validate with proper backtesting
   </li>
   <li>
    Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness
   </li>
   <li>
    Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making
   </li>
  </ul>
  <li>
   Deep Learning
  </li>
  <ul>
   <li>
    Build and train deep learning models using PyTorch or TensorFlow/Keras
   </li>
   <li>
    Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)
   </li>
  </ul>
  <li>
   Evaluation, Explainability, and Iteration
  </li>
  <ul>
   <li>
    Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports
   </li>
   <li>
    Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence
   </li>
  </ul>
  <li>
   Productionization &amp; MLOps (Project-Dependent)
  </li>
  <ul>
   <li>
    Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration
   </li>
   <li>
    Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans
   </li>
  </ul>
  <li>
   Documentation &amp; Communication
  </li>
  <ul>
   <li>
    Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders
   </li>
   <li>
    Create documentation and lightweight demos that make results actionable
    <br/>
   </li>
  </ul>
 </ul>
 Success in This Role Looks Like
 <br/>
 <br/>
 <ul>
  <li>
   You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)
  </li>
  <li>
   Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring
  </li>
  <li>
   Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)
  </li>
  <li>
   Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)
  </li>
  <li>
   Strong SQL skills (joins, window functions, aggregation, performance awareness)
  </li>
  <li>
   Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset
  </li>
  <li>
   Hands-on experience across multiple model types, including:
  </li>
  <ul>
   <li>
    Classification &amp; regression
   </li>
   <li>
    Time series forecasting
   </li>
   <li>
    Clustering/segmentation
   </li>
  </ul>
  <li>
   Experience with deep learning in PyTorch or TensorFlow/Keras
  </li>
  <li>
   Strong problem-solving skills: ability to work with ambiguous goals and messy data
  </li>
  <li>
   Clear communication skills and ability to translate analysis into decisions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)
  </li>
  <li>
   Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)
  </li>
  <li>
   Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)
  </li>
  <li>
   Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)
  </li>
  <li>
   Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)
  </li>
  <li>
   Consulting or client-facing delivery experience
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Certifications (Strong Plus)
  <br/>
  <br/>
 </strong>
 Candidates with at least one relevant certification are especially encouraged to apply:
 <br/>
 <br/>
 <ul>
  <li>
   Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks)
  </li>
  <li>
   Databricks certifications (Data Scientist, Data Engineer, or related)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)
  </li>
  <li>
   Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products
  </li>
  <li>
   Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  <em>
   Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
   <br/>
   <br/>
  </em>
 </em>
 Important: Immigration Sponsorship Policy
 <br/>
 <br/>
 Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including:
 <br/>
 <br/>
 <ul>
  <li>
   Direct Company Sponsorship: Such as H-1B, J-1, or TN visas
  </li>
  <li>
   Employer of Record: Listing Fusemachines as the immigration employer on any government documentation
  </li>
  <li>
   Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT)
   <br/>
   <br/>
  </li>
 </ul>
 Powered by JazzHR
 <br/>
 <br/>
 qUN1H2divA
</div>


Machine Learning Engineer / Data Scientist

Turing

<div>
 <p>
  <strong>
   About Turing
  </strong>
 </p>
 <p>
  Based in San Francisco, California, Turing is the world&rsquo;s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&amp;L.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Role Overview
  </strong>
 </p>
 <p>
  Turing is looking for Venture Capital professionals to work with our researchers to improve the performance of AI models. You will apply your expertise in startup evaluation, funding rounds, cap table management, and early-stage market analysis to evaluate and train AI systems. If you enjoy solving complex problems in venture capital and are interested in shaping the future of AI in finance, please apply. No prior AI experience is required.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What Does Day-to-Day Look Like
  </strong>
 </p>
 <ul>
  <li>
   Evaluate LLM models on venture capital topics such as startup valuation, term sheet analysis, cap table modeling, and market sizing.
  </li>
  <li>
   Create rubrics to assess model capabilities on tasks like due diligence for early-stage companies, funding round structuring, and portfolio construction for VC funds.
  </li>
  <li>
   Collaborate with AI researchers and fellow finance experts to shape training methods, evaluation strategies, and benchmarks.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <ul>
  <li>
   2+ years of experience in Venture Capital (e.g., seed/Series A&ndash;C investing, VC fund operations, or startup advisory).
  </li>
  <li>
   Strong grasp of startup valuation methods, term sheet negotiation, cap table mechanics, and venture fund economics.
  </li>
  <li>
   Excellent English written communication.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Bonuses (Not at All Necessary)
  </strong>
 </p>
 <ul>
  <li>
   CFA (Level I/II/III), MBA in Finance, or operational experience at a high-growth startup.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Perks of Freelancing with Turing
  </strong>
 </p>
 <ul>
  <li>
   Work on the cutting edge of AI and finance.
  </li>
  <li>
   Fully remote and flexible work environment.
  </li>
  <li>
   Competitive hourly compensation of ~$100+/hour depending on experience.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Offer Details
  </strong>
 </p>
 <ul>
  <li>
   Commitment: Flexible, 10&ndash;30 hrs/week.
  </li>
  <li>
   Duration: ~1 month, with the possibility of extension based on performance and project needs.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   After applying, you&rsquo;ll receive a login link by email. Please complete your profile promptly so we can proceed with your application.
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   We&rsquo;re actively hiring for this role. If you know exceptional talent, please refer them at
   <u>
    turing.com/referrals
   </u>
   and earn money for successful referrals.
  </strong>
 </p>
</div>


Remote Venture Capital Analyst ($100/hr)

Colgate-Palmolive

<div></div><div><div><div>Requisition ID <b>174332</b> - Posted <b>06/18/2026</b> - <b>Analytics</b> - <b>United States</b> - <b>New York</b> - <b>New York</b> - <b>Colgate-Palmolive</b> - <b>Travel - up to 10% of time</b> - <b>On-site</b></div></div><p></p><div><div><div><div><p><b><br>
</b></p></div></div></div></div><br>
<div></div><div><div><div><div><div><div><div>No Relocation Assistance Offered<br>
Job Number #174332 - New York, New York, United States<br>
<br>
<b>Who We Are</b><br>
<br>
Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!<br>
<br>
Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values&mdash;Caring, Inclusive, and Courageous&mdash;we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.</div><br>
<div><b>*This role can sit in our Park Ave (NYC) or Piscataway, NJ office*</b></div><br>
<div></div>
<div><b>
Role Summary</b></div>
<p>
We are seeking a Machine Learning Engineer who brings the analytical rigor of a data scientist and the engineering discipline of a software architect. In support of Colgate-Palmolive&rsquo;s purpose to Make More Smiles and our commitment to a healthier future for our people, pets, and planet, this role builds the advanced machine learning capabilities that power smarter decisions, accelerate innovation, and create measurable impact across our global enterprise.</p>
<p>
As part of the Enterprise AI/ML Center of Excellence, you will lead the architectural design and end-to-end execution of high-priority ML initiatives. This involves integrating statistical modeling, optimization, and autonomous workflows into Colgate-Palmolive's business processes to accelerate innovation, enhance decision intelligence, and embed AI. Beyond hands-on technical work, you ensure solutions are architecturally sound, production-ready, and compliant with enterprise governance standards, translating strategy into robust execution aligned with stakeholder needs and long-term value creation.</p><br>
<div></div>
<div><b>
Responsibilities:</b></div>
<ul>
<li><div>Productionize ML Research: Transition experimental models into robust, scalable production services. You don't just build the model; you build the pipeline that sustains it.</div>
</li>
<li><div>Pipeline Orchestration: Design and maintain complex data and ML pipelines using Airflow and dbt to ensure data integrity and model reliability.</div>
</li>
<li><div>Statistical Rigor: advanced statistical modeling and hypothesis testing to validate models, ensuring outcomes are testable and honest.</div>
</li>
<li><div>DevOps &amp; MLOps: Utilize modern developer tools to work within and CI/CD frameworks for ML and software lifecycle management</div></li></ul><br>
<div>
</div><div><b>Required Qualifications:</b></div>
<ul>
<li><div>Bachelor&rsquo;s Degree (or higher) in a high-rigor field: Statistics, Physics, Chemistry, Mathematics, Data Science, or Computer Science with a heavy emphasis on Statistical Learning.</div>
</li>
<li><div>Experience: Bachelors degree: 6+ of years of technical experience; Masters or PhD (3+ years)</div></li></ul><br>
<div>
</div><div><b>Preferred Qualifications:</b></div>
<ul>
<li><div>Proven expertise in Data Science and/or Machine Learning Engineering.</div>
</li>
<li><div>Advanced proficiency in Python (Production-grade) and SQL.</div>
</li>
<li><div>Hands-on experience with Airflow for orchestration and dbt for transformation.</div>
</li>
<li><div>Familiarity with modern IDEs and Agentic Coding systems (e.g., Cursor, Windsurf, Claude Code, Antigravity) to maximize output velocity.</div>
</li>
</ul><ul><li><div>Modern Stack: Expert knowledge of Python, Scikit-learn, major ML Libraries</div>
</li>
<li><div>Data Engineering: Deep understanding of data lifecycle (ETL/ELT), data architecture, best practices for templatized data transformation</div>
</li>
<li><div>Engineering Excellence: Familiar with Docker/Kubernetes, CI/CD, Git, and &quot;Software Engineering for ML&quot; best practices.</div>
</li>
<li><div>LLM Literacy: Familiar with concepts underpinning LLMs, and strategies to integrate GenAI into MLE project lifecycle</div></li><br>
</ul>
<div><br>
<b>Compensation and Benefits</b><br>
Salary Range $130,000.00 - $170,000.00 USD<br>
<br>
Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.<br>
<br>
Benefits: Salaried employees enjoy a comprehensive benefits package, including medical, dental, vision, basic life insurance, paid parental leave, disability coverage, and participation in the 401(k) retirement plan with company matching contributions subject to eligibility requirements. Additional benefits include a minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours) and 13 paid holidays (vacation days are prorated based on the employee's hire date within the calendar year). Paid sick leave is adjusted based on role and location in accordance with local laws. Detailed information regarding paid sick leave entitlements will be provided to employees upon hiring and may be subject to adjustments based on changes in legislation or company policies.<br>
<br>
<b>Our Commitment to Inclusion</b><br>
Our journey begins with our people&mdash;developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business.<br>
<br>
<b>Equal Opportunity Employer</b><br>
Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law.<br>
<br>
Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation.<br>
<br>
For additional Colgate terms and conditions, please click here.<br>
<br>
#LI-On-site</div></div></div></div></div></div></div></div><p></p>

Machine Learning Engineer (174332)

Mercor

<div>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 <strong>
  Mercor
 </strong>
 connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
 <strong>
  Benchmark
 </strong>
 ,
 <strong>
  General Catalyst
 </strong>
 ,
 <strong>
  Peter Thiel
 </strong>
 ,
 <strong>
  Adam D'Angelo
 </strong>
 ,
 <strong>
  Larry Summers
 </strong>
 , and
 <strong>
  Jack Dorsey
 </strong>
 .
 <br/>
 <br/>
 <strong>
  Position:
 </strong>
 ML Engineer (Coding Agent Experience)
 <br/>
 <br/>
 <strong>
  Type:
 </strong>
 <strong>
  Contract
  <br/>
  <br/>
 </strong>
 <strong>
  Compensation:
 </strong>
 <strong>
  $85/hour
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 <strong>
  Remote
  <br/>
  <br/>
 </strong>
 <strong>
  Role Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
  </li>
  <li>
   Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
  </li>
  <li>
   Identify bugs, edge cases, performance issues, and failure modes in AI models.
  </li>
  <li>
   Compare outputs from multiple frontier models and assess their strengths and weaknesses.
  </li>
  <li>
   Apply professional engineering judgment to realistic ML engineering scenarios.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <strong>
  Must-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   2+ years of professional machine learning engineering experience.
  </li>
  <li>
   Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
  </li>
  <li>
   Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
  </li>
  <li>
   Ability to evaluate model-generated machine learning implementations and technical tradeoffs.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience deploying ML systems to production.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compensation &amp; Legal
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   $400 per accepted task
  </li>
  <li>
   Compensation is tied to accepted work.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Application Process (Takes 20&ndash;30 mins to complete)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Upload resume
  </li>
  <li>
   AI interview based on your resume
  </li>
  <li>
   Submit form
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Resources &amp; Support
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  </li>
  <li>
   For any help or support, reach out to: support@mercor.com
   <br/>
   <br/>
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  PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
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AI/ML Engineer - Fully Remote | Upto $85/hr

CVS Health

<div><p>We&rsquo;re building a world of health around every individual &mdash; shaping a more connected, convenient and compassionate health experience. At CVS Health&reg;, you&rsquo;ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger &ndash; helping to simplify health care one person, one family and one community at a time.</p><p></p><div>
Position Summary: Caremark LLC, a CVS Health company, is hiring for the following role in New York, NY: Sr Data Scientist to formulate and apply mathematical and computational modeling methods towards data extraction and manipulation. Duties include: design and develop data solutions using industry leading tools, technologies and best practices to profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business; develop advanced algorithms and statistical predictive models to evaluate scenarios and provide usable information on health metrics and potential future outcomes; extract and manipulate data from multiple large data sources and deliver predictive models that inform solutions for in-house teams (i.e. pharmacy pricing, medical costs, risk scores, onboarding) and customer engagement across critical journeys (i.e. calories, heart rate, breast cancer, maternity); utilize strong programming skills to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems; support deployment of insights across multiple channels and work on mathematical analysis methods, machine learning, and statistical analyses. Telecommuting available. Multiple positions.<br>
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Requirements: Master&rsquo;s degree (or foreign equivalent) in Computer Science, Data Science, Operations Research, Statistics, Mathematics, Analytics, or a related field and two (2) years of experience in<br>
each of the following:<br>
<ul><li>R, Python, or SQL;</li><li>Visualization tools, including PowerBI or Tableau;</li><li>&ldquo;Big data&rdquo; platforms including Hadoop (Azure, GCP, or AWS) and Spark, Airflow, Kafka, Hbase, Pig, or NoSQL;</li><li>Translating analytical problems into structured programs using PySpark, Scala, PL/SQL or Teradata BTEQ;</li><li>Machine Learning or NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP);</li><li>Data analytics on large data sets in healthcare, business, or retail sector;</li><li>Marketing analytics, clinical trials, or health research;</li><li>Containerized services, storage, and workspace management;</li><li>Featuring engineering, model training, hyperparameter tuning, distributed model training, and supervised and unsupervised learning implementation; and</li><li>Qualitative analysis techniques, including clustering, repression, and pattern recognition.</li></ul><br>
Pay Range: $111240.00/year to $222480.00/year.</div><p></p><p>
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company&rsquo;s equity award program.<br>
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In addition to your compensation, enjoy the rewards of an organization that puts our heart into caring for our colleagues and our communities. The Company offers a full range of medical, dental, and vision benefits. Eligible employees may enroll in the Company&rsquo;s 401(k) retirement savings plan, and an Employee Stock Purchase Plan is also available for eligible employees. The Company provides a fully-paid term life insurance plan to eligible employees, and short-term and long term disability benefits. CVS Health also offers numerous well-being programs, education assistance, free development courses, a CVS store discount, and discount programs with participating partners. As for time off, Company employees enjoy Paid Time Off (&ldquo;PTO&rdquo;) or vacation pay, as well as paid holidays throughout the calendar year. Number of paid holidays, sick time and other time off are provided consistent with relevant state law and Company policies.<br>
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<b>Great benefits for great people</b></p><p></p><p>
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.</p><br>
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.<p><br>
Additional details about available benefits are provided during the application process and on Benefits Moments.</p><br>
This job does not have an application deadline, as CVS Health accepts applications on an ongoing basis.<p></p><p>
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.</p></div>

Sr Data Scientist

NYU Langone Health

<div><p>NYU Grossman School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge.
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<i>For more information, go to</i> <i>med.nyu.edu</i>, and interact with us on <i>LinkedIn</i>, <i>Glassdoor</i>, <i>Indeed</i>, <i>Facebook</i>, <i>Twitter</i> <i>and</i> <i>Instagram</i>.</p>
<p><b>
Position Summary:</b><br>
We have an exciting opportunity to join our team as a Research Associate.
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In this role, the successful candidate is responsible for conducting independent basic science experimentation based on research conducted in the assigned laboratory under the mentorship of a senior scientist. Individual is expected to seek to build a portfolio of research accomplishments in preparation for acquiring a higher degree in biomedical research or medicine.</p>
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Job Responsibilities:</b></p>
<ul>
<li>After a period of time working in the laboratory, the candidate will be expected to train graduate students and post-doctoral fellows in experimental design, technique and performance.</li>
<li>Generates hypotheses and designs and performs experiments to test them.</li>
<li>Executes multiple experiments simultaneously over time independently.</li>
<li>Records all experimental findings in a laboratory notebook, analyze and interpret experimental findings.</li>
<li>Based on results, independently suggests and tests modifications to protocols.</li>
<li>Prepares figures and diagrams for presentations and publications.</li>
<li>Communicates results and collaborates with other professionals in the lab.</li>
<li>Demonstrates a significant level of intellectual input into the design of the project.</li>
<li>Presents findings at lab meeting, responds to challenges, and participates in exchanges of ideas to advance the science.</li>
<li>Reads and understands relevant scientific literature.</li>
<li>Contributes to the preparation of articles on research outcomes and progress and to the submission of same for publication.</li>
<li>Participates in the editing and proofing of grant proposals, annual grant reports, and manuscripts for publication and recommends modifications to the Principal Investigator.</li></ul><br>
<p></p>
<p><b>
Minimum Qualifications:</b><br>
To qualify you must have a College graduate with a B.S. or B.A. in Biomedical or Physical Sciences. A minimum commitment of two years is required and placement in position may not exceed three years.</p>
<p><b>
Preferred Qualifications:</b><br>
Prior research experience in a laboratory setting.</p>
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Qualified candidates must be able to effectively communicate with all levels of the organization.</i>
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NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.
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NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.
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View Know Your Rights: Workplace discrimination is illegal.</p>
<p>
NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $47,033.89 - $50,000.00 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.</p>
<p>
To view the Pay Transparency Notice, please click here</p></div>

Research Associate - Mazzoni Lab

Explore 265+ Ai training research scientist est in New York this July. Find roles across top companies and apply now to boost your career.