Jobs at Fractal

The Senior Data Scientist will lead AI/ML projects, manage a data science team, implement analytical solutions, and leverage data for business insights.

The Data Modeler is responsible for designing and architecting enterprise data applications, focusing on data modeling, strategy, and warehouse development.

As a Fullstack Senior Engineer, you will develop and maintain frontend and backend applications for data-driven projects, collaborating with a multidisciplinary team on API integrations and user interface designs.

Responsible for architecting and developing full stack enterprise applications, collaborating with multiple teams, and mentoring junior engineers.

Consult with CPG/FMCG clients on Revenue Growth Management analytics programs, focusing on pricing strategies, promotion analysis, and optimizing revenue growth while leading engagements across diverse global markets.

Lead design and delivery of end-to-end integrations for an Invoice-to-Cash platform. Define APIs, data contracts, canonical models, and event-driven workflows. Integrate ERPs, banking APIs, EDI/SFTP/email ingestion, and AI engines. Build monitoring, reconciliation, and governance; lead an integration engineering team to ensure scalable, secure, and automated financial reconciliation.

Lead technology strategy and architecture for data and cloud-native solutions on GCP; engage senior client stakeholders, guide delivery teams, ensure end-to-end execution, mentor engineers, and drive scalable, secure data and ML platforms.

Design, develop, and maintain interactive Power BI dashboards; perform ETL and data modeling; write complex DAX; conduct exploratory analysis; collaborate with stakeholders to translate requirements into BI solutions; ensure data accuracy, security, and performance; present insights to non-technical audiences.

Lead and run enterprise data governance: develop frameworks, policies, metadata and lineage, lead data quality remediation, define stewardship and ownership, ensure regulatory compliance (GDPR/CCPA), set KPIs, train staff, and manage a governance team.

The Data Steward ensures data governance and quality by developing solutions, creating data metrics, conducting profiling, and collaborating with stakeholders to maintain data integrity.

Design and scale enterprise Agentic and Generative AI platforms, focusing on microservices, orchestration, reliability, and cloud architecture. Lead teams to develop production-ready AI systems.

Drive business growth by selling consulting and technical services, managing client relationships, and collaborating with Microsoft for joint sales opportunities.

This role involves planning and designing Azure infrastructure, developing cloud solutions, mentoring teams, and ensuring cloud security and compliance.

The Engagement Manager will lead analytics-driven programs, manage client relationships, and innovate solutions in decision science and AI. Responsibilities include fostering collaboration, mentoring teams, and contributing to practice growth.

The AWS Data Engineer will work on designing and building cloud-based solutions, utilizing AWS services, and integrating systems for clients. Requires experience with various AWS tools and Java development.

The Senior Fullstack Engineer will design, develop, and maintain enterprise web applications while collaborating with data teams and managing junior engineers.

The Sr. Data Scientist will lead the implementation of AI solutions, focusing on multi-agent GenAI workflows, LLM orchestration, and scalable applications while ensuring quality and governance in delivery.

Gather and analyze client requirements, identify gaps, and develop BI dashboards using Qlik Sense/QlikView, Power BI, or Tableau. Present dashboards and storylines to end users, collaborate with distributed teams, and manage multiple projects under pressure.

Owner of full-stack feature implementation across web, API, cloud, DevOps, and AI-enabled capabilities. Design, build, test, deploy, monitor, and optimize scalable, secure production systems; integrate LLMs and RAG; enforce code quality, mentor juniors, and collaborate with architects, TPMs, product, QA and platform teams.

Advise clients on developing and implementing data governance strategies. Design policies, frameworks, and practices for data quality, privacy, metadata management, and security. Deliver governance projects, build capability with frameworks and accelerators, and promote governance awareness across stakeholders and committees.