{"id":3831895,"url":"https://alion.io/job/qualifacts-manager-business-intelligence","title":"Manager, Business Intelligence","company":{"id":2084708,"name":"Qualifacts","domain":"qualifacts.com","url":"https://alion.io/company/qualifacts","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":93,"open_postings":4,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vadodara, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"dbt","optional":false},{"name":"HIPAA","optional":false},{"name":"Least Privilege","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-11-05T19:35:30Z","employer_posted_date":null,"last_verified_at":"2026-11-05T19:35:30Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"This is an onsite position, 5 days/week, in the Vadodara office working the night shift. Hours are 6:30pm-3:30am IST. Remote applicants will not be considered.\n\nRCM Business Intelligence Strategy and Leadership:\nOwn the RCMS BI roadmap and demand portfolio, aligning priorities with service performance, customer value, growth, automation, and scalability; manage intake, capacity, delivery, and stakeholder communication.\nServe as the RCM BI subject-matter expert and trusted advisor, translating business questions into measures, insights, and actionable recommendations.\nLead and develop BI analysts and developers; establish standards across the analytics lifecycle and replace recurring ad hoc reporting with reusable data products.\n\nRCM Analytics and Performance Intelligence:\nDeliver analytics across charge capture, claim submission, clean claims, rejections, denials, payments, remittances, underpayments, A/R aging, days revenue outstanding, collections, first-pass resolution, productivity, quality, backlog, turnaround time, customer retention, and cost-to-serve.\nUse root-cause, cohort, trend, variance, funnel, segmentation, and predictive analyses to identify payer, client, platform, workflow, staffing, training, quality, and upstream drivers; quantify financial and operational impact.\nDevelop work-prioritization and exception-management insights; partner with Revenue Optimization and operations leaders to validate findings, target high-value opportunities, and measure sustained improvement.\n\nSnowflake, Data Modeling, and Analytics Engineering:\nOwn governed Snowflake data products, including dimensional and semantic models, reusable views, data marts, metric layers, and curated datasets.\nWrite and review advanced SQL and transformations; optimize query performance, workloads, and consumption while controlling data grain, duplication, lineage, and reconciliation risks.\nPartner with data engineering and platform teams on ingestion, orchestration, transformation, and monitoring using dbt, Airflow, APIs, and approved technologies; maintain definitions, dictionaries, source-to-target logic, ownership, refresh expectations, and support documentation.\n\nBI Tools, Visualization, and Self-Service Analytics:\nLead Power BI dashboard, semantic model, measure, and report development using strong modeling, DAX, visualization, accessibility, performance, security, and deployment practices.\nApply common design standards across Power BI, Sigma, Tableau, Looker, and other approved tools; deliver intuitive executive, operational, client, and analyst experiences without duplicative reporting.\nEnable self-service analytics through certified datasets, governed models, role-based access, documentation, and training; manage dashboard ownership, usage, enhancement, retirement, and support.\n\nData Governance, Quality, and Controls:\nOwn RCMS KPI and reporting governance, including approved formulas, sources, dimensions, exclusions, refresh schedules, targets, and accountable owners; communicate assumptions, limitations, and quality issues.\nEstablish automated quality checks, reconciliations, anomaly detection, release validation, and production monitoring with documented thresholds and remediation; enforce source control, peer review, testing, environment separation, and change documentation.\nProtect patient, customer, employee, and financial data through role-based access, least privilege, masking, secure development, and compliance with HIPAA, privacy, security, and company requirements.\n\nAI, Automation, and Scalable Growth:\nPrioritize AI, machine learning, RPA, intelligent automation, and workflow orchestration opportunities that reduce manual effort, detect revenue leakage, improve work prioritization, and increase capacity.\nEnable analytics for approved RCMS platforms and develop reusable, configurable data products that scale across clients, platforms, service lines, and geographies.\nUse approved AI-assisted tools with human review, data protection, accuracy, and auditability; define investment business cases, acceptance criteria, baselines, adoption plans, and benefit tracking.\n\nStakeholder and Customer Enablement:\nPartner with RCMS Operations, Revenue Optimization, Finance, Product, Technology, Customer Success, IQuality, Compliance, and client-facing teams on requirements, process mapping, metric definitions, prototypes, user acceptance testing, adoption, and outcome measurement.\nDeliver concise executive and client-ready narratives explaining performance, causes, impact, and recommended actions; provide training, office hours, documentation, and data literacy support.\n\nQualifications of the Manager, Business Intelligence - RCM:\nBachelor’s degree in computer science, Information Systems, Data Analytics, Healthcare Analytics, Finance, Engineering, or a related field; advanced degree preferred.\n6+ years in BI, analytics engineering, reporting, or data analytics, including leadership of projects, analysts, or developers.\nHealthcare revenue cycle analytics experience covering claims, 837/835 transactions, remittances, denials, payments, A/R, payer behavior, reimbursement, and productivity.\nAdvanced SQL and direct Snowflake experience, including modeling, transformation, optimization, data-quality validation, and reusable datasets.\nStrong direct Power BI skills in semantic modeling, DAX, Power Query, dashboard design, performance, security, deployment, and support; other BI tools beneficial.\nExperience with transformation, integration, and orchestration tools such as dbt, Airflow, APIs, Python, R, or comparable approved technologies.\nExperience with data governance, KPI standards, lineage, access controls, testing, source control, releases, and production monitoring.\nPreferred: AI, machine learning, RPA, intelligent automation, or workflow analytics experience in a controlled business environment; experience in healthcare technology, RCM services, BPO, shared services, or multi-client environments.\n\nKnowledge, Skills, and Abilities:\nRCM domain expertise: Connects healthcare billing, payer, claims, denial, remittance, payment, A/R, collection, revenue leakage, productivity, and customer-performance concepts to useful analytics.\nAnalytics architecture: Designs trusted data products from source ingestion through Snowflake modeling, semantic layers, BI delivery, governance, and user adoption.\nBusiness intelligence development: Applies Power BI and modern BI best practices to create accurate, maintainable, performant, accessible, and reusable analytics.\nAnalytical problem solving: Uses structured root-cause analysis, statistics, segmentation, trend analysis, and hypothesis testing to distinguish signal from noise and translate findings into action.\nData governance and quality: Builds durable metric definitions, lineage, reconciliation, access, testing, monitoring, and change-control practices.\nAI and automation fluency: Understands appropriate applications, limitations, controls, and value measures for AI, machine learning, RPA, and AI-assisted analytics development.\nFinancial and operational acumen: Connects analytics to cash, revenue, margin, cost-to-serve, capacity, client value, contractual performance, and scalable growth.\nLeadership and talent development: Sets standards, coaches technical talent, plans capacity, improves delivery discipline, and creates accountability for quality and outcomes.\nExecutive communication: Explains complex data and technical concepts clearly to non-technical leaders, operating teams, and client stakeholders.\nProduct and change mindset: Manages analytics as products with defined users, outcomes, roadmaps, adoption measures, lifecycle ownership, and continuous improvement.\nSkills\nBI, Business Intelligence, Power BI, 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