• Translate business needs into data requirements: work directly with business stakeholders to capture, clarify and prioritise analytical requirements, ensuring alignment between strategic goals and technical execution. • Own the full analytics delivery lifecycle: from scoping data needs and coordinating with data engineering, to building models, dashboards and reports in the relevant tooling, to presenting findings and insights to leadership. • Lead the OneView Dashboard initiative: consolidate KPIs from across the business (revenue, free subscriptions, campaign performance, web traffic, and more) into a unified, reliable reporting layer for one of our key SaaS brands. • Coordinate with data management and modelling teams to ensure timely delivery. • Drive the GTM Funnel Analytics programme: support the design and delivery of a centralised Go-To-Market funnel tracking system, covering lead acquisition, channel performance, and marketing automation across a portfolio of SaaS brands. • Expand analytics maturity over time: once GTM tracking is established for initial brands, extend the framework to include onboarding flows and product usage analytics, progressively enriching the analytical picture across the portfolio. • Act as a cross-functional enabler: proactively unblock dependencies across Data Platform, Analytics, BI, and Marketing automation Engineering — bringing the seniority and breadth of experience to contribute meaningfully across all these domains without hand-holding. • Collaborate with data tooling: work hands-on with the existing data stack (including Databricks, and BI/visualisation tools as required) and contribute to how data is modelled, structured and surfaced for business consumption.

Role Description We are seeking a Sr. Data Analyst to support enterprise reporting, dashboard development, and applied data analysis for an evolving analytics project. This role will focus on Tableau reporting, SQL/Python analysis, data cleaning and preparation, and translating business questions into meaningful insights and outcomes. Enterprise experience strongly preferred. - Build, maintain, and support enterprise-level reporting and dashboards in Tableau. - Work with complex and sensitive datasets, including salary-related data. - Use SQL and Python to perform data analysis, analytical deep dives, and data preparation. - Take business questions and translate them into insights, conclusions, and actionable outcomes. - Own data cleaning responsibilities to ensure datasets are accurate, usable, and analysis-ready. - Apply foundational statistics to support analysis where needed. - Work within an evolving project environment with curiosity, flexibility, and a willingness to learn. - Collaborate with data engineering partners and understand data flow across systems, even though API automation will be handled by the Data Engineer. Qualifications - Strong applied data analysis experience using Python. - Python data cleaning experience. - SQL experience. - Tableau experience, including enterprise reporting and dashboard work. - Snowflake experience. - Ability to analyze business questions and produce meaningful insights. - Experience preparing, cleaning, and working with complex datasets. - Foundational understanding of statistics. Requirements - Experience working with HR data. - Experience working with sensitive data, such as salary or compensation data. - Understanding of data flow across systems. - Familiarity with BigQuery. - Exposure to AWS or similar cloud environments. Benefits - Remote role open to LATAM-based contractors. - US hours overlap required. - Full-time contract engagement. - Expected allocation is 40 hours per week. - Contract expected to run through March 31, 2027.

Role Description - Analyze large volumes of Medicaid healthcare data, including claims, enrollment, provider, eligibility, encounter, and pharmacy data. - Gather, analyze, and document business and data requirements from Medicaid business stakeholders. - Develop and maintain complex SQL queries, stored procedures, and data validation scripts for data extraction and analysis. - Perform detailed analysis of Medicaid claims adjudication, member eligibility, provider networks, and reimbursement processes. - Design, develop, and maintain dashboards, scorecards, and reports using BI tools such as Tableau, Power BI, or Cognos. - Conduct data profiling, data quality assessments, and root cause analysis to ensure accuracy and completeness of Medicaid data. - Collaborate with business teams to support Medicaid regulatory reporting, including CMS, state-specific mandates, and quality measures. - Analyze healthcare KPIs, utilization trends, cost containment opportunities, and operational metrics. - Support Medicaid programs such as Managed Care, Fee-for-Service (FFS), Dual Eligible, LTSS, and Value-Based Care initiatives. - Work closely with ETL and data engineering teams to validate source-to-target mappings and data transformations. - Perform impact analysis for system enhancements, regulatory changes, and Medicaid policy updates. - Create functional specifications, business requirement documents (BRDs), and data mapping documents. - Participate in Agile ceremonies including sprint planning, backlog grooming, daily stand-ups, and retrospectives. - Ensure compliance with HIPAA regulations and healthcare data security standards. - Provide mentorship and guidance to junior analysts and team members. Qualifications - Strong experience in Medicaid programs and healthcare payer systems. - Deep understanding of Medicaid claims processing lifecycle. - Experience with: - Member Eligibility and Enrollment - Claims Adjudication - Provider Management - Encounters and Capitation - Prior Authorization - Care Management - Pharmacy and PBM data - ICD-10, CPT, HCPCS, DRG, NDC coding systems - CMS and State Medicaid reporting Requirements - 10+ Years of experience. Company Description

Role Description We are looking for a Predictive Analytics Analyst to join a newly established, high-impact team focused on transforming enterprise decision-making. This team is at the forefront of delivering timely, accurate, and forward-looking financial and operational insights by combining advanced analytics, actuarial concepts, automation, and AI-enabled capabilities. In this role, you will help build predictive analytics capabilities from the ground up in a fast-paced, “startup-like” environment within a large organization. You will play a key role in designing and implementing data-driven solutions that drive profitable growth, improve operational efficiency, and strengthen business intelligence across the enterprise. This is an excellent opportunity for a data-driven professional who enjoys autonomy, thrives in ambiguous environments, and wants to influence how analytics is built and scaled. What You’ll Do - Develop and implement predictive models using advanced statistical and machine learning techniques (e.g., regression, clustering, decision trees, neural networks) - Build and maintain programs for predictor and response variables, ensuring model accuracy and scalability - Partner with business stakeholders to understand needs, translate them into analytical solutions, and communicate actionable insights clearly - Present analytical findings to non-technical audiences, explaining methodologies, data sources, and business impact - Explore, prepare, and structure large datasets (internal and external) to support model development and enhancement - Contribute to the design and continuous improvement of modeling frameworks, processes, and best practices - Ensure data quality and model integrity through rigorous validation and review processes - Develop a strong understanding of the data landscape, including sourcing, mapping, and integrating data across systems - Support enterprise data initiatives (e.g., data migration and transformation programs) - Collaborate with and mentor junior analysts, sharing knowledge and promoting best practices - Stay current on industry trends, particularly within insurance analytics and predictive modeling Qualifications - 6+ years of experience in predictive analytics, data science, or related field - Bachelor’s degree in Mathematics, Statistics, Computer Science, or related field - Professional experience in insurance or pricing analytics is a strong plus Requirements - Strong experience with Python, R, and SQL - Experience with SAS is a plus - Advanced knowledge of predictive modeling and machine learning techniques - Statistical analysis and data mining - Data preparation and feature engineering - Strong understanding of data ecosystems and ability to navigate complex data environments - Ability to translate complex data into clear, actionable insights - Excellent communication skills, with the ability to present analytical findings to diverse audiences - Problem-solving mindset with the ability to work independently in a fast-evolving environment - Experience contributing to or building analytics capabilities from scratch is highly valued - Collaborative and proactive approach, with a willingness to share knowledge and mentor others - Experience working with cross-functional teams in data-driven environments Benefits - Competitive compensation and benefits package - Comprehensive benefits package - Career development and training opportunities - Flexible work arrangements - Dynamic and inclusive work culture within a globally renowned group - Private Health Insurance - Pension Plan - Paid Time Off - Training & Development