Data Scientist

• Design, develop, and deploy machine learning and statistical modeling solutions for complex financial and insurance business problems
• Build predictive models using regression, classification, clustering, segmentation, ensemble methods, time-series forecasting, anomaly detection, and propensity modeling
• Perform exploratory data analysis, hypothesis testing, statistical inference, feature engineering, feature selection, model validation, and performance analysis
• Analyze large-scale structured and unstructured datasets to identify patterns, trends, risk drivers, and actionable business insights
• Develop analytics and machine learning solutions for underwriting, claims, fraud/risk detection, customer segmentation, pricing, retention, forecasting, and portfolio analytics
• Design and develop Generative AI and LLM-based applications, including document analysis, summarization, knowledge retrieval, intelligent search, and conversational AI
• Build RAG pipelines using embeddings, semantic search, vector databases, and enterprise knowledge sources
• Apply prompt engineering, few-shot learning, prompt tuning, LoRA/PEFT, and fine-tuning where appropriate
• Evaluate ML and GenAI solutions across accuracy, precision, recall, F1-score, ROC-AUC, model stability, hallucination, relevance, latency, and cost
• Collaborate with business stakeholders, data engineers, ML engineers, MLOps, and product teams to translate business requirements into scalable analytical and AI solutions
• Communicate analytical findings and model outcomes to technical and business stakeholders, focusing on business impact and decision support
• Support productionization, monitoring, governance, and continuous improvement of ML and GenAI solutions

Senior Data Scientist

• Implement models and analyses supporting drug discovery and development activities
• Develop quantitative biomarkers from imaging and phenotype data
• Develop disease progression and time-to-event (survival) models
• Conduct real-world-data analyses
• Partner with clinical development and biostatistics teams on pre-specified and exploratory analyses
• Support clinical trial design and interpretation using real-world data
• Collaborate on cross-functional analyses with genomics, clinical research, and biology teams
• Develop and implement improvements and extensions to the data platform
• Build analytic pipeline modules and interactive analysis tools across AMD and glaucoma programs
• Contribute to data and analytics strategic planning and roadmap
• Contribute to scientific publications
• Communicate data science work to internal and external stakeholders

Data Scientist I – II

• Build and curate the knowledge base for a generative AI/ML research effort
• Develop data and knowledge extraction pipelines for machine learning models
• Extract, structure, and validate design knowledge into knowledge graphs and ontologies
• Engineer metadata, annotation, and provenance for program datasets
• Analyze results, laboratory measurements, and simulation output to produce actionable findings
• Design, build, populate, and maintain research knowledge bases under version control with provenance tracking
• Develop rule-based, statistical, and ML-assisted pipelines that convert unstructured and semi-structured sources into structured, queryable knowledge
• Establish quality metrics and validation procedures for extracted content
• Engineer metadata, annotation schemas, and packaging for synthetic, simulated, and real datasets
• Perform exploratory and inferential analysis on training data, simulation output, and evaluation results
• Build dashboards and reports showing where generated waveforms succeed or fail against objectives
• Feed findings back to AI model researchers and engineers
• Contribute data and analysis sections to design reviews, monthly status reports, and dataset documentation
• Coordinate with academic subcontractors on shared data and knowledge resources

• Lead the sizing, targeting, launch, and performance evaluation of marketing campaigns designed to improve member outcomes and engagement
• Develop audience segmentation, propensity models, and targeting strategies for engagement interventions
• Design and measure experiments, A/B tests, and incentive programs to optimize member activation, product adoption, retention, and health outcomes
• Analyze member behavior across digital products and healthcare touchpoints
• Build predictive and prescriptive models informing campaign strategy, reward structures, and personalized member experiences
• Partner with Product, Marketing, Care Management, and Operations teams on analytics-driven engagement solutions
• Establish KPIs and measurement frameworks for campaign performance, ROI, member engagement, and clinical impact
• Communicate insights, recommendations, and performance results to senior stakeholders and business leaders
• Lead cross-functional initiatives scaling successful engagement strategies at enterprise level
• Collaborate with Data Engineering and MLOps teams to operationalize targeting models and automate campaign execution and measurement
• Foster experimentation and continuous optimization using data-driven decision-making and behavioral science principles

Manager – Data Scientist

• Develop and evaluate predictive, machine learning, natural language processing, or generative AI solutions for complex healthcare and business challenges
• Translate claims, member information, call transcripts, surveys, and web logs into actionable insights
• Partner with data scientists, engineers, business leaders, and clinical stakeholders to define problems, test ideas, and turn research into scalable solutions
• Build reproducible data pipelines, models, and visualizations
• Communicate findings, tradeoffs, and recommendations to technical and nontechnical audiences
• Present work to senior leadership when opportunities arise
• Seek feedback, test assumptions, document methods, and consider data quality, privacy, fairness, and model performance
• Contribute to healthcare analytics projects such as predictive health models, NLP platforms, conversational AI, transformer-based classification, OCR, and large language model research

Data Scientist Intern – Master's Program

• Provide technical leadership across the overall Analytics function, potentially with an enterprise mandate
• Support US FCRM (Financial Crimes Risk Management) and TD’s Data Governance Process
• Provide strategic and day-to-day direction for complex AML Data Governance program activities
• Provide operational support and address or escalate related issues
• Oversee timely execution of periodic and event-driven reviews for regulatory alignment
• Work independently on analysis, design, and support of technical data management solutions
• Manage and prioritize multiple projects and longer-range functional planning
• Work with business owners to identify opportunities and serve as a data science ambassador
• Translate business problems into viable data science solutions
• Extract and prepare data, apply statistics and advanced analytics, and derive insights from big data
• Visualize data insights and communicate results to technical and non-technical stakeholders
• Collaborate with analysts, software engineers, data engineers, and application developers on scalable data science solutions
• Provide analytical thought leadership and educate the organization on hypothesis testing and statistical validation
• Improve business processes and implement continuous improvement activities
• Participate in cross-functional and enterprise initiatives as a subject matter expert
• Identify risks, provide guidance, and implement action or remediation plans
• Monitor service, productivity, efficiency, and performance improvements
• Manage relationships with business lines, corporate functions, control functions, and stakeholders
• Monitor emerging issues, trends, and regulatory requirements
• Maintain risk management and control processes aligned with risk appetite
• Participate in knowledge transfer, mentoring, cross-training, and team development
• Keep stakeholders informed about project status and relevant day-to-day information
• Build productive relationships with internal and external business partners
• Act as a brand ambassador for TD and the business area

Data Scientist jobs in New Jersey

Senior Data Scientist

Data Scientist I – II

Data Scientist

Manager – Data Scientist

Data Scientist Intern – Master's Program

Data Scientist III