About the Role We are looking for a Staff Data Scientist (Product Analytics) to build and lead product analytics end-to-end at Salla. In this role, you will own event instrumentation standards, tracking plans, and the measurement scaffolding that ensures every product launch, feature change, and checkout optimization is grounded in reliable data. You will establish Salla’s experimentation framework — defining how we run A/B tests, set guardrail metrics, conduct SRM checks, and think about statistical power and minimum detectable effects. Beyond methodology, you will partner closely with Product and Engineering to ensure measurement is baked into the development lifecycle, not bolted on after the fact. This role is ideal for someone who believes great product decisions start with great data, and who wants to build the analytical backbone of the largest e-commerce enabler in Saudi Arabia. Responsibilities - Define and enforce event instrumentation standards and tracking plans across web, mobile, and backend systems - Own core product funnel definitions (e.g., merchant onboarding, checkout, subscription conversion) and ensure they are accurately tracked, monitored, and understood - Build and operationalise Salla’s experimentation framework, including: - Experiment design guidance (metrics, guardrails, randomisation units) - Statistical methodology (frequentist and/or Bayesian, sequential testing where appropriate) - SRM checks, pre-experiment power analysis, and MDE calibration - Post-experiment synthesis and decision documentation - Ensure trustworthy, reproducible reporting of experiment results — including clear communication of confidence levels, practical significance, and trade-offs - Partner with Product Managers and Engineers to embed measurement into the product development lifecycle, from PRD through to post-launch review - Conduct deep-dive product analyses (retention drivers, feature adoption, user segmentation) that shape the product roadmap - Collaborate with the Data Platform team on data quality, pipeline reliability, and self-serve analytics tooling for product teams - Mentor product analysts and foster a culture of analytical rigour, intellectual honesty, and curiosity Nice to Have - Proficiency working in Arabic - Based in Saudi (Jeddah, Makkah) - Experience in e-commerce, marketplace, or SaaS product analytics - Familiarity with experimentation platforms (e.g., Eppo, Statsig, LaunchDarkly, Optimizely, or internal tooling) - Experience with BI tools (Looker, Metabase, or equivalent) and modern data stacks (dbt, ClickHouse, BigQuery) - Knowledge of Bayesian methods, sequential testing, or multi-armed bandit approaches - Experience working in the GCC

About the Role Liquid Web is hiring a Data Scientist to power our volumetric, subscription-driven growth engine (hosting, commerce, and software). This role owns the models and measurement systems connecting marketing spend to conversion, retention, and LTV, with a critical emphasis on ICP-specific economics (agencies, SaaS, ecommerce, and mission-critical buyers). You aren’t just a "dashboard builder." You are a Data Anthropologist. You look past the rows in Snowflake to see the human stories—the friction points that cause churn, the "aha" moments that trigger an upgrade from VPS to Dedicated, and the behavioral patterns that separate a hobbyist from a mission-critical enterprise buyer. You’ll build and operationalize LTV and churn models, develop marketing attribution approaches, and partner across Marketing, Product, RevOps, and Finance. You will also help hire and lead a reporting team, setting the standard for metrics, dashboards, and governance in Power BI. This Job is For You If: - You speak "Finance" and "Creative" fluently. You can explain $LTV$ to a CFO and conversion attribution to a Copywriter without losing the soul of either. - You are a "Pattern Hunter." You don't just report that churn happened; you find the "Silent Churn" indicators three months before the customer even thinks about canceling. - You loathe "Vanity Metrics." You find no joy in "Total Page Views." You live for Contribution Margin and Cohort Payback Periods. - You’re a Power BI Poet. Your DAX is elegant, your star schemas are pristine, and your dashboards tell a story so clear that an executive can understand the "Why" in under ten seconds. What You’ll Do - Subscription Economics & LTV Modeling: Build predictive LTV models accounting for upgrades, churn, and margin. Develop payback and CAC views to support budget allocation and align with Finance on contribution LTV and time horizons. - Expansion Strategy (Upsell & Cross-sell): Model the triggers and pathways for account expansion. Develop propensity-to-buy models for add-ons (security, storage, backups) and build data-driven upgrade paths (e.g., VPS to Dedicated) to maximize customer wallet share. - ICP & Segmentation Modeling: Define and operationalize ICP segmentation using firmographic, behavioral, and intent signals. Create a decision framework to quantify ICP-specific retention, plan mix, and support costs. - Attribution & Measurement: Design multi-touch attribution (MTA) models calibrated with incrementality methods like geo-tests and holdouts. Improve full-funnel measurement from first touch through activation and retention. - Data Foundation & Reliability: Partner with Marketing Ops to ensure clean event tracking (GTM, dataLayer, UTMs). You'll be the guardian of the dataLayer, ensuring that what we see in GTM actually reflects reality in Snowflake. - Power BI Reporting & Governance: Own executive-ready reporting, including KPI scorecards and cohort views. Maintain semantic models using DAX, ensuring star schema design, query folding, and incremental refreshes for scalability. - Team Leadership: Help hire and coach a reporting and analytics team. Establish operating rhythms (WBR/QBR) and set standards for dashboard design, documentation, and storytelling. What Success Looks Like (6–12 Months) - Liquid Web utilizes a defensible LTV and payback model for all spend decisions. - LTV:CAC and payback are reported accurately by both ICP and channel. - Expansion metrics (upsell/cross-sell velocity and attachment rates) are visible and actionable for Marketing and Sales. - Power BI serves as the governed, trusted "source of truth" across the organization. Required Qualifications - Experience: 5+ years in Data Science or Growth Analytics within a subscription-based business. - Modeling: Proven track record building LTV, churn, and ICP segmentation models tied to revenue outcomes. - Revenue Growth: Demonstrated ability to analyze and optimize upsell/cross-sell funnels and product attachment rates. - Tech Stack: Advanced SQL and proficiency in Python/R. Expert-level Power BI (DAX and semantic modeling) and experience with Snowflake (or similar cloud warehouses). - Instrumentation: Familiarity with GTM tags, event schemas, and the flow of web/billing data into a warehouse. - Communication: Strong cross-functional leadership and executive-ready presentation skills. Nice-to-Have - Experience in hosting, cloud infrastructure, or developer-led products. - Pricing and packaging analytics (promo impact, add-on attachment). - Knowledge of privacy-centric measurement (server-side tagging, modeled conversions). Working Style - Builder Mindset: Comfortable moving from messy data to reliable, automated systems. - The "So What?" Specialist: You never deliver a chart without an insight. You understand that data without a recommendation is just noise. - Pragmatic: Knows when a calibrated "good enough" measurement beats a complex, fragile model. - Collaborative Leader: Able to influence without authority and level up a team through high standards. Work Environment The physical demands described here are representative of those that must be met by an individual to successfully perform the essential duties of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential duties. - While performing the essential duties of this job, the individual is regularly required to speak and hear - While performing the essential duties of this job, the individual is regularly required to use hands for keyboarding, gross manipulation, and fine manipulation - Works at a desk and computer screen for extended periods of time - Works in a traditional climate controlled office environment or from home - Works in a highly stressful environment dealing with a wide variety of challenges, deadlines and diverse employee population Disclaimer This job description is only a summary of the typical functions of the position. It is not intended to be an exhaustive or comprehensive list of all job responsibilities, tasks, or duties. Additional duties and tasks may be assigned as part of the job function. Liquid Web Inc. reserves the right to modify, interpret, or apply this job description in a way that best supports the organizational needs. The job description in no way creates or implies an employment contract. The employment contract remains “at will”. Equal Employment Opportunity Policy: Liquid Web is committed to offering equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic.

Our Benefits: Our team members enjoy a robust benefits package including: - Competitive compensation - Paid time off for vacations, holidays, and illness - Comprehensive health insurance (medical, dental, vision, prescription) - 401(k) retirement savings plan - Education support and student loan assistance - Life and disability insurance - Flexible spending account Job Summary We are seeking a highly specialized and experienced Oracle Enterprise Data Scientist to drive data quality, standardization, and insight generation across our core Oracle operational suite. This role serves as the authoritative expert on translating complex, high-volume data from Oracle Supply Chain Management (SCM), Oracle Procurement, Oracle Revenue Cycle Management (RCM), and Oracle Inventory into actionable business intelligence. The successful candidate will be focused on ensuring absolute data integrity—a critical function in a regulated healthcare environment—and transforming raw transactional data into high-value operational reports, interactive dashboards, and predictive models that optimize cost-per-case, enhance inventory accuracy, and accelerate the revenue cycle. Essential Functions 1. Data Validation, Integrity, and Compliance (Critical Focus) - Healthcare Data Quality Assurance: Design and implement automated data validation frameworks specific to healthcare operations, ensuring transactional data (e.g., supply usage, procedure charging, contract pricing) is accurate. - Compliance Verification: Develop reports and monitoring tools to detect anomalies and discrepancies that could impact regulatory reporting, financial audits (e.g., SOX implications), or compliance with GPO contracts and payer rules. - Revenue Leakage Identification: Specifically focus on validating the link between inventory consumption (SCM) and patient billing (RCM) data to prevent charge capture errors, ensuring accurate patient bills and maximizing appropriate reimbursement. - Root Cause Analysis: Investigate and diagnose data errors originating in Oracle system configurations (EBS or Fusion), ensuring the integrity of critical data points like item master definitions, vendor codes, and pricing tiers. 2. Standardized Operational Analytics and Reporting - KPI Development (Healthcare Specific): Define, standardize, and institutionalize critical operational metrics across the organization, such as: - Inventory Accuracy Rate for Critical Supplies - Procurement Compliance Rate (Off-Contract Spend) - Days of Supply (DOS) for high-value pharmaceuticals and implants - Cost-Per-Case Variance analysis (linking supply cost to procedure type) - Claims Denial Rate Analysis linked to operational inputs - High-Value Reporting: Develop and maintain standardized operational reports and interactive dashboards (e.g., Tableau, Power BI) focused on optimizing the efficiency and spend within the OR, Clinics, and centralized purchasing departments. - Executive Insights: Create visually compelling and accurate reports for executive leadership on the overall health and financial performance driven by Oracle system outputs. 3. Advanced Modeling and Process Optimization - Predictive Inventory Modeling: Develop sophisticated models to forecast demand volatility (e.g., flu season spikes, pandemic-related surges) for critical supplies and pharmaceuticals, minimizing shortages and excess waste. - Revenue Cycle Modeling: Build predictive models to forecast cash flow, anticipate denials based on procurement/charging patterns, and prioritize RCM work queues based on expected return. - Efficiency Optimization: Utilize machine learning techniques to optimize logistics (e.g., warehouse routing, supply replenishment schedules) and procurement processes (e.g., automated purchase order generation based on consumption velocity). 4. Collaboration and System Expertise - Serve as the technical data expert for functional Oracle teams (Finance, Clinical Operations, Materials Management), bridging the gap between business needs and data structure. - Document data lineage, metric definitions, and model methodologies to ensure transparency and trust in derived insights across the enterprise. Required Qualifications: - Education: Master’s degree in Data Science, Health Informatics, Statistics, Industrial Engineering, or a related quantitative field. - Experience: 2+ years of experience in a specialized data science, BI, or analytics role, working within a large healthcare system, hospital, or payer environment. - Deep Oracle Domain Expertise (Mandatory): Proven practical experience analyzing, querying, and understanding the complex data models within at least two of the following Oracle applications (EBS or Fusion): - Oracle Supply Chain Management (SCM) & Inventory: Specific understanding of item masters, warehouse transactions, and consumption data. - Oracle Procurement: Expertise in purchase order data, contract management, and vendor performance metrics. - Oracle Revenue Cycle Management (RCM): Understanding of charge capture, billing, and the data linkage to operational inputs. Technical Proficiency: - Expert-level SQL skills for complex database querying, including experience navigating Oracle tables/views. - Proficiency in Python or R, with experience in statistical modeling, time series analysis, and machine learning libraries. - Experience developing advanced visualizations using industry-leading tools (Tableau, Power BI). - Demonstrable experience working with large-scale Enterprise Data Warehouses (EDW) in a regulated environment. - Preferred Skills and Attributes - Familiarity with clinical coding standards (CPT, ICD-10) as they relate to procedure costing and RCM data. - Understanding of HIPAA, HITECH, and general healthcare data governance standards. - Experience with advanced analytics applied to surgical services or procedural areas. - Excellent collaboration and communication skills, with the ability to present complex analytical findings to clinical and executive audiences. - Certification in Oracle applications or cloud platforms is a plus. This is a fully remote opportunity This position is not eligible for immigration sponsorship now or in the future. Applicants must be authorized to work in the U.S. for any employer. We know it’s not just about finding a job. It’s about finding a place where you are respected, valued and where your work is purposeful and fulfilling. A place where your talent is recognized, professional development is encouraged and career advancement is possible. Community Health Systems is one of the nation's leading healthcare providers. With healthcare delivery systems in 36 distinct markets across 14 states, CHS operates 69 affiliated hospitals with more than 10,000 beds and approximately 1,000 other sites of care, including physician practices, urgent care centers, freestanding emergency departments, imaging centers, cancer centers, and ambulatory surgery centers.

• Desenvolver, validar e implementar modelos preditivos e algoritmos de machine learning • Realizar análises estatísticas avançadas e modelagem matemática aplicada a problemas de negócio • Trabalhar com grandes volumes de dados, estruturados e não estruturados • Construir e otimizar pipelines de dados escaláveis • Atuar na automação de processos analíticos e implementação de práticas de MLOps • Monitorar, avaliar e realizar o retreinamento de modelos em produção • Avaliar e propor novas ferramentas, tecnologias e abordagens analíticas • Comunicar resultados e insights de forma clara para públicos técnicos e não técnicos • Atuar com autonomia na definição de abordagens analíticas em cenários complexos