Jobs at Quantiphi

Leads software product development projects and advanced analytics, machine learning, and technology solution delivery. Responsibilities include gathering requirements, defining problems, creating user stories, managing project teams and client expectations, preparing technical documentation, applying Agile and Scrum methodologies, identifying risks, consulting clients, and developing creative solutions and presentations.

Administer and optimize Workday HCM, including business processes, workflows, calculated fields, security, reports, dashboards, tenant configuration, and release management. Partner with stakeholders to implement enhancements, troubleshoot issues, perform testing, maintain system integrity, and support end users. The role also requires ticketing and case management experience, strong analytical and communication skills, and familiarity with multiple Workday modules.

Leads data preparation, profiling, and exploratory analysis for large-scale datasets; builds, evaluates, tunes, and deploys time-series forecasting models for demand planning. The role requires Python, SQL, AWS, SageMaker, ML frameworks, and MLOps tools. It involves independent end-to-end ownership, customer presentations, stakeholder collaboration, and translating technical work into business outcomes. Retail or e-commerce forecasting and computer vision experience are preferred. Travel to the Bengaluru client office twice weekly is required.

Develop and fine-tune traditional machine learning and predictive models for regression, classification, sales forecasting, and growth prediction. Prepare and unify data from multiple sources, perform exploratory data analysis and feature engineering, evaluate model performance, and use Python, Jupyter, and AWS services including S3 and Redshift. Present model outputs and insights to business stakeholders while working independently with client teams.

Architect, develop, deploy, and monitor scalable machine learning and LLM-powered conversational AI systems on AWS. Lead agent framework, tool-calling, multi-agent, RAG, MLOps, analytics, and observability development while collaborating with technical and business stakeholders.

Build and maintain large-scale Snowflake data platforms and pipelines, including AWS and legacy-platform migrations. Develop SQL, Spark, PySpark, and Python transformations; implement batch and streaming workflows; optimize Snowflake performance; and apply security, governance, and data-sharing capabilities. Support migration validation, troubleshooting, monitoring, production operations, SDLC, CI/CD, and stakeholder collaboration while using Snowflake AI and migration tools.

Build, deploy, and maintain production-grade machine learning systems on Google Cloud Platform. Develop generative AI applications, RAG systems, agentic and multi-agent workflows, traditional ML, and computer vision solutions. Own MLOps practices including CI/CD, testing, model versioning, deployment, monitoring, and drift detection. Build APIs, microservices, knowledge graphs, and semantic search systems while collaborating with architects, data engineers, analysts, and enterprise clients.

Design and develop enterprise Master Data Management solutions using Profisee, Informatica MDM, or Reltio. Build scalable ingestion, integration, transformation, ETL/ELT, and publishing pipelines; implement cleansing, matching, deduplication, survivorship, hierarchy, and data quality rules. Integrate MDM platforms with databases, APIs, data lakes, warehouses, and applications. Troubleshoot production issues, maintain mappings and documentation, collaborate with stakeholders, support delivery activities, and mentor junior data engineers.

Develop machine learning architectures, models, data pipelines, and production systems using Python, PySpark, SQL, AWS, NLP, LLMs, and Generative AI. Collaborate with engineers, analysts, delivery managers, and clients to deliver measurable business outcomes. Communicate insights, identify sales opportunities, mentor junior engineers, manage client relationships, and support project delivery.

Develop high-level machine learning architectures, build and productionize models and end-to-end ML systems, and deliver data-driven insights for clients. The role involves Python, PySpark, SQL, NLP, LLM, GenAI, statistical modeling, cloud services, and data pipeline development. Responsibilities also include client relationship management, mentoring junior engineers, coordinating delivery teams, identifying sales opportunities, and communicating business impact.

Design and deliver large-scale data pipelines and storage/compute solutions on Google Cloud. Build ingestion and processing jobs for terabyte/petabyte workloads, create cloud migration strategies, troubleshoot distributed systems, and develop automation, testing, and monitoring tooling. Collaborate with cloud, software, ML, and operations teams and contribute to proposals and solution designs while ensuring data modeling and governance.

Design and implement scalable enterprise data platforms, ETL/ELT pipelines, data warehouses and lakes. Define data models, governance, security, and architecture standards. Collaborate with product, BI, and data science teams, provide production support, mentor engineers, and evaluate emerging technologies and POCs.

Leads requirements gathering, process mapping, data analysis, solution design, stakeholder communication, and testing support for healthcare provider technology projects. Focus areas include EHR integration, revenue cycle management, patient engagement, clinical workflows, compliance, interoperability, and value-based care. Creates project documentation, supports UAT, manages business and technical alignment, and mentors junior analysts.

Lead Oracle database migrations to AWS, ensuring minimal downtime and optimized performance. Responsibilities include database tuning, pipeline building, and managing S3 data lakes.

The Associate Lead will oversee QA and MLOps for AI systems, defining testing strategies, validating ML lifecycles, and leading quality initiatives with AWS services.

Lead Platform Engineering to architect, deploy, and manage secure, scalable AWS cloud infrastructure using IaC, CI/CD, monitoring, automation, and container platforms; enforce AWS security governance; mentor engineers and collaborate on solution design.

Design, develop, and maintain scalable analytics solutions on the Looker BI Platform, focusing on LookML modeling and collaboration with data engineers and stakeholders.

The Data Modeler designs and maintains the Common Data Model and source-to-target mappings for healthcare data assets, working closely with engineers and clinical informaticists to ensure accuracy and integrity in data representation.

Design and maintain scalable analytics solutions on Looker BI Platform, optimize data models, develop dashboards, and ensure governance and compliance with data standards.

The Data Architect is responsible for designing data architecture, leading the creation of the Common Data Model, ensuring standards compliance, and handling high-volume data ingestion while collaborating closely with technical and governance teams.