Part Time Data Scientist Machine Learning Jobs in New York

Specialised Part-Time Consulting OpportunityWe are sharing a specialised part-time consulting opportunity for experienced data science and analytics professionals with strong expertise in machine learning, statistical modelling, experimentation, data infrastructure, business intelligence, and enterprise analytics.This role supports advanced AI evaluation work focused on realistic large-scale data science and analytics workflows. Selected professionals will design complex technical scenarios, develop reference outputs, and create evaluation rubrics that reflect how experienced data scientists and analytics leaders approach modelling, experimentation, data strategy, and production-scale data systems.Key ResponsibilitiesMachine Learning & Predictive ModellingDevelop realistic scenarios involving predictive modelling and machine learning developmentCreate tasks covering feature engineering, model selection, training, validation, and performance evaluationAssess modelling approaches for statistical validity, scalability, and business relevanceIdentify weak assumptions, methodological issues, and potential sources of bias or leakageProduce reference analyses and model documentation demonstrating strong technical judgementStatistical Analysis & ExperimentationDevelop tasks involving statistical inference, A/B testing, experimentation, and causal analysisEvaluate experimental designs, metrics, sampling approaches, and statistical conclusionsCreate scenarios involving ambiguous or noisy real-world datasetsAssess whether analytical conclusions are adequately supported by available evidenceProduce reference analyses explaining methodological choices and limitationsData Engineering & Analytics InfrastructureCreate scenarios involving enterprise data pipelines, data transformation, and analytics infrastructureApply familiarity with platforms such as Snowflake, Databricks, and comparable data environmentsDevelop tasks involving SQL, Python, R, and large-scale data-processing workflowsEvaluate data architecture and pipeline decisions for reliability, scalability, and analytical usabilityIdentify data-quality, lineage, governance, and integration issuesBusiness Intelligence & Decision SupportDevelop scenarios involving enterprise reporting, dashboards, and business intelligenceCreate tasks using tools such as Tableau, Power BI, or comparable analytics platformsEvaluate metrics, visualisations, and analytical outputs for clarity and decision usefulnessTranslate complex analytical findings into actionable business insightsProduce reference executive-level analyses and recommendationsMLOps & Production AnalyticsDevelop scenarios involving deployment, monitoring, validation, and lifecycle management of machine learning modelsApply familiarity with platforms such as SageMaker, Vertex AI, MLflow, or comparable toolsEvaluate model-monitoring strategies, retraining approaches, and production performanceAssess operational risks including model drift, data changes, and reliability issuesApply MLOps best practices to realistic enterprise machine learning environmentsData Strategy & GovernanceCreate tasks involving enterprise data strategy, analytics governance, and cross-functional decision-makingEvaluate approaches to data quality, privacy, access, governance, and analytical consistencyDevelop scenarios involving competing stakeholder and business requirementsAssess strategic trade-offs across technical capability, risk, cost, and organisational prioritiesProduce reference recommendations reflecting senior-level data and analytics judgementAI Evaluation & Rubric DevelopmentDesign expert-level evaluation tasks across data science and analytics workflowsDraft reference outputs demonstrating authentic professional technical judgementDevelop rubrics that distinguish experienced data science reasoning from generic textbook or tutorial-level responsesReview AI-generated outputs for statistical accuracy, technical quality, and practical relevanceIdentify subtle analytical errors, unsupported conclusions, and unrealistic technical recommendationsProvide clear written rationale supporting evaluation decisionsIdeal Profile5+ years of professional experience in data science, analytics, machine learning engineering, or a closely related fieldExperience as a Data Scientist, Analytics Lead, Machine Learning Engineer, or comparable technical professionalDirect ownership of production machine learning systems, analytics initiatives, data products, or large-scale analytical projectsStrong proficiency in Python or R and SQLExperience with platforms such as Snowflake, Databricks, SageMaker, Vertex AI, MLflow, or comparable technologiesFamiliarity with Tableau, Power BI, or other enterprise business-intelligence toolsStrong understanding of statistical modelling, experimentation, A/B testing, model validation, and causal inferencePractical experience with data pipelines, MLOps, data governance, and production analyticsAbility to communicate complex technical and analytical reasoning clearly and precisely in writingExperience developing technical documentation, training content, evaluation rubrics, or model documentation is advantageousEngagement DetailsPart-time independent contractor engagementFully remoteFlexible scheduling based on project requirementsCompensation: $50–$60/hourProjects may be extended, shortened, or concluded based on project needs and performanceWork must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third partyH1-B and STEM OPT support is unavailable for this engagementAbout the PlatformThis opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy.