Top Tech Jobs & Startup Jobs in NYC, NY

Leads credit risk forecasting for a US credit card acquisition program. Responsibilities include building response and balance curves, developing forecasting methodologies, evaluating Value Matrix assumptions, benchmarking predictive performance, recommending optimization enhancements, designing champion-challenger testing, and presenting recommendations to senior leadership. The role also manages client relationships and supports business development through analytics, modeling, and risk consulting services.

Leads end-to-end analytics projects, including requirements gathering, data pipelines, machine learning model development and deployment, BI dashboards, reporting automation, data quality, and stakeholder delivery. Optimizes SQL performance, deploys models on GCP, documents methodologies, supports business development, and mentors analytics teams.

Leads advanced analytics and data engineering projects in data governance. Designs scalable data quality tools, develops large-scale data pipelines, performs analysis, and delivers data-driven insights to clients and senior executives. Uses Python, SQL, Spark, SAS, and statistical methodologies for data processing, deployment, and documentation. Manages project delivery, gathers requirements, facilitates client feedback, and presents findings. The role requires a master’s degree and four years of data engineering and analytics experience.

Provides executive and administrative support to the CHRO and HR leadership team while coordinating HR transformation, AI adoption, and process-improvement projects. Responsibilities include calendar and travel management, meeting organization, executive communications, project planning, stakeholder follow-up, user testing, progress tracking, risk escalation, reporting, and confidential information handling.

Leads the architecture, development, modernization, and optimization of enterprise Databricks Lakehouse platforms. Designs batch and real-time pipelines, implements Spark and PySpark solutions, and establishes governance, data quality, security, monitoring, and CI/CD practices. Provides technical leadership, mentors engineering teams, manages delivery risks, and translates business requirements into scalable cloud data solutions across Azure, AWS, or GCP. Supports analytics, AI/ML, and business intelligence initiatives while optimizing platform performance, cost, reliability, and compliance.

Leads enterprise-scale Databricks Lakehouse architecture, data platform modernization, and batch or real-time ETL/ELT development. Designs scalable Spark and PySpark solutions across cloud platforms, establishes governance, security, quality, lineage, and observability standards, and drives CI/CD and infrastructure automation. Provides technical leadership through architecture and code reviews, mentoring, stakeholder engagement, delivery planning, and executive communication. Supports analytics, AI/ML, and business intelligence ecosystems while optimizing platform performance, reliability, and cost.

Build and support end-to-end data pipelines using Fivetran, Snowflake, and dbt. Develop data models, tests, documentation, incremental processes, and optimized SQL. Manage Snowflake security and data-loading patterns, implement data quality monitoring, troubleshoot production issues, and support CI/CD deployments. Collaborate with technical and business teams to onboard data sources and deliver enterprise data products. Python, orchestration, AWS, and AI-assisted development experience are beneficial.

Analyze customer behavior, segmentation, clickstream data, attribution, and marketing campaign performance. Design A/B tests, apply statistical modeling using SQL, Python, and SAS, and develop automated Tableau dashboards and reporting. Provide actionable insights to improve customer acquisition, retention, engagement, and marketing ROI.

Leads end-to-end data engineering initiatives, including Azure Databricks development, SQL-to-PySpark migration, data integration, automation, and analytics solutions. Manages client requirements, developer teams, stakeholder alignment, quality control, compliance, performance evaluation, and strategic data sourcing. The role also involves managing risk analytics projects and ensuring adherence to organizational policies.

Lead end-to-end marketing strategy for strategic ecosystem partnerships, including annual planning, co-marketing campaigns, demand generation, budget management, pipeline attribution, executive reporting, events, and partner enablement. Collaborate with partner leads, marketing teams, AI and industry marketing, events, and leadership to grow joint pipeline and revenue while strengthening EXL’s AI and data positioning.