The Principal Architect will manage large-scale data analytics engagements, design solutions for clients, lead discussions on technology and architecture, and oversee product development lifecycles. The role requires collaboration with various teams and strong communication to deliver robust data solutions in a global delivery model.

As a Principal Data Engineer (Azure), you will design and build scalable data ingestion pipelines, implement data lakes, and collaborate with teams to deliver analytical solutions using Azure and Big Data technologies.

The Data Analyst role involves discovering and analyzing data requirements, creating process models, and improving data quality. The position requires experience in financial planning and analysis, data profiling, and collaboration with data engineers to document and communicate requirements effectively.

The Data Analyst will analyze data requirements, develop data models, analyze business processes related to financial planning, and improve data quality. Responsibilities include data profiling and system analysis to identify patterns and enhance data models.

The Principal Data Scientist will lead statistical analysis and machine learning projects, develop tailored models, present findings to stakeholders, mentor junior team members, and manage multiple projects to drive data-driven decision-making.

The Recruiter will manage end-to-end recruitment processes, build candidate relationships, collaborate with hiring managers, create job postings, interview candidates, and maintain accurate records in the ATS to ensure effective talent acquisition.

The Senior Data Analyst will analyze business requirements, design and develop Tableau reports, conduct data analysis, and collaborate with stakeholders to deliver effective business intelligence solutions. This role focuses on enhancing user experience and optimizing performance through efficient dashboard creation and data representation.

As a Machine Learning Engineer, you will deploy and validate Machine Learning Engine solutions, create scalable systems, build production data pipelines, and write production-quality code. Collaboration with various teams will be key as you leverage analytical skills to deliver business value and communicate results.

The Business Analyst Lead will manage analytics projects focused on the insurance industry, collaborate with stakeholders to solve business problems using analytics, and present solutions to senior management. Strong communication and project management skills are essential, along with expertise in SQL, Python, and visualization tools like Tableau and PowerBI.

The Sr Consultant / Manager will focus on supply chain analytics, developing optimization models, conducting data analysis, and managing projects in supply chain optimization. Responsibilities include crafting transit mappings, establishing product cost mappings, and collaborating with teams to drive data-driven solutions.

The role involves managing credit policy integration and forecasting, performing variance analysis, and reporting insights to senior management, with a focus on credit card policies in the banking sector.

The Sr. Consultant/Manager - Credit Risk Policy role involves integrating credit policy decisions into forecasting, conducting variance analysis, and using various risk models. The candidate will also report key insights to senior management and must have hands-on coding skills within the banking and financial services sector, specifically in credit cards.

The Consultant - Credit Risk will develop and validate loss forecasting models, analyze historical loss data, collaborate with cross-functional teams for effective model application, and prepare reports on model performance and analytical insights.

The Business Analyst will work with credit and consumer lending stakeholders to evaluate processes, identify inefficiencies, and implement solutions. Responsibilities include cross-functional collaboration, project management, and translating technical data into actionable strategies.

As an ML Ops Architect, you will implement scalable systems and manage ML and data pipelines. You will collaborate with cross-functional teams to deploy models, ensure governance and compliance, and monitor performance. You will leverage cloud technologies and best practices in MLOps to enhance ML capabilities across the organization.

The Senior Data Scientist will develop and deliver advanced analytics and ML solutions, optimize data pipelines, monitor ML infrastructure, and collaborate with data and ML engineers in a CI/CD environment, focusing on deploying AI-driven innovations.

The Technology Partner at Tiger Analytics is responsible for providing thought leadership and client engagement, overseeing data initiatives, and creating technology solutions. This role involves mentoring staff, managing architecture resources, and collaborating with clients on data and process improvements. Key responsibilities include pre-sales activities, generating solutions and proposals, and leading engineering talent in data-driven transformations.

The Sr. Consultant/Manager - Credit Risk Strategy is responsible for developing and implementing credit risk strategies, utilizing advanced analytics to assess risk trends, collaborating with cross-functional teams, and preparing executive reports for senior management.

As a Senior Data Scientist, you will develop analytical models and collaborate with cross-functional teams to address business objectives. You'll leverage machine learning techniques to create scalable models, advocate for data-driven decision making, and engage with a team of Data Scientists while staying updated with industry trends.

The Power BI Analyst will leverage expertise in Power BI and SQL to build self-service dashboards and analyze large data sets. The role involves coordinating with stakeholders to gather requirements, proposing KPIs, and applying insights to solve business challenges. Experience in pharma commercial reporting and familiarity with ETL processes is preferred.