Purpose:

Building an AI‑first organisation is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI‑enabled, cloud‑based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and testing environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities. Operating across more than 30 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI‑enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve, must drive an AI first sense of purpose and urgency.

As a senior business analyst, you will be responsible for designing, operating, and continuously improving product intelligence systems utilizing AI-enabled analytics and agent technology, driving business outcomes across growth, retention, predictability, and product quality. This role owns metric architecture, root-cause analysis, and closed-loop improvement cycles that convert data and AI-generated insights into decisions and sustained performance gains.

Outcomes You Will Drive:

• Increased decision velocity through AI-assisted analytics, automated insights, and self-service metrics.

• Identify, lead, and deliver high-impact improvements across the business using Six Sigma methods, including AI-supported root cause analysis and continuous improvement.

• Drive business lifecycle process change to reduce churn drivers, delivery bottlenecks, and forecast variance via data- and AI-informed root-cause analysis.

Core Responsibilities:

Product Intelligence & KPI Governance

• Own KPI architecture including definitions, lineage, SLAs, and decision use-cases, supported by AI-assisted metric validation.

• Instrument and monitor leading indicators such as activation, time-to-value, adoption depth, and quality using automated and AI-driven monitoring.

• Operationalize metrics as products with versioning, change control, and documentation.

Root Cause Analysis & Continuous Improvement

• Lead structured RCA using 5 Whys, Fishbone, Pareto, and statistical analysis, augmented by AI-assisted pattern detection.

• Translate findings into corrective actions across processes, backlogs, and operating models.

• Run closed-loop improvement cycles (measure → diagnose → improve → control).

• Apply process engineering techniques including process mapping and value-stream mapping.

Revenue Modeling, Planning & Forecasting

• Partner with Finance, Sales Operations, and Services/Customer Success Operations to support product-level ARR/MRR reporting across new, expansion, contraction, and churn motions.

• Assist with maintaining forecast inputs and assumptions, including pipeline signals, adoption trends, onboarding throughput, and time-to-value metrics.

• Produce plan-versus-actual variance analyses and contribute data-driven insights to inform corrective actions and prioritization discussions.

Analytics & Experimentation

• Build decision-oriented dashboards in Power BI or Tableau.

• Define measurement plans for experiments and feature rollouts.

• Use AI tooling to automate analysis and accelerate insight generation.

Operating Cadence & Business Reviews

• Design product business reviews focused on decisions and corrective actions.

• Deliver concise pre-reads highlighting risks, root causes, and AI-informed recommendations.

Delivery & Quality Signal Integration

• Analyze delivery and reliability metrics and link them to customer impact.

• Identify systemic bottlenecks and recommend throughput improvements.

Data & Instrumentation Enablement

• Validate telemetry and KPI alignment with Data and Engineering teams, including AI-readiness of data sources.

• Lead RCA on data quality issues to eliminate recurrence.

• Automate recurring reporting through reusable data models.

Success Metrics

• KPI trust and adoption across leadership and product forums.

• Reduced time from question to insight to action, supported by AI automation.

• Measured improvements in activation, retention drivers, and expansion signals.

• Improved forecast accuracy and early risk detection.

• Sustained reduction in recurring reporting and data issues.

Required Qualifications

• 3+ years in Product Ops, Product Analytics, BizOps, RevOps, or FP&A analytics (or equivalent impact).

• Strong SQL and data modeling skills; experience with semantic layers.

• Advanced BI experience with Power BI and/or Tableau.

• Demonstrated leadership of RCA and cross-functional corrective actions.

• Continuous improvement or process engineering experience (Lean, Six Sigma, Kaizen); Green Belt strongly preferred.

Preferred

• Lean Six Sigma Green Belt (or higher).

• Experience with experimentation platforms and causal measurement.

• Familiarity with product instrumentation and delivery tooling (e.g., Azure DevOps).

• Experience applying AI tools for analytics automation with governance.

• Working knowledge of DORA and reliability engineering metrics.

Operating Principles

• Proactively surface risks and opportunities using data and AI.

• Fix systems, not symptoms.

• Automate repeatable work.

• Be decision-oriented.

• Maintain metric trust through governance and transparency.

Travel:

Up to 20% international travel for internal meetings.

Supervisory Responsibilities:

None.

Benefits:

Our benefits for Full Time employees are designed to help you move forward in your career, and in areas of your life outside of work. From health and wellness benefits, 401 (k) Savings Plan, stock incentive programs, paid time off, parental leave, and tuition assistance, we've got you covered with our total rewards package.

The starting pay range for a candidate selected for this position who is generally within the range of $88,208 - $100,000 for annual base salary. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay may be above or below this range.

Clinisys’s Commitment to Equal Opportunity:

Clinisys Information systems is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.

General Guidance:

This job description is meant to provide an accurate depiction of tasks and accountabilities that are most often associated with this role. While we strive to provide an accurate depiction, nothing in this description restricts the company from changing, reassigning, expanding or reducing scope of accountabilities and is subject to change at any time.