Job Description

Senior Data Analyst – Global Customer Support (AI-Driven)

Location: India (Bangalore or Kolkata)
Reports To: SVP, Global Support

The Senior Data Analyst transforms global support data into actionable insights that drive operational performance, customer satisfaction, and strategic decisions. This role combines advanced analytics with AI-driven capabilities to shift support operations from reactive reporting to predictive, data-led decision-making.

Clinisys' AI Philosophy:

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

Key Responsibilities

Data Analysis & Insights

• Analyse support data (cases, SLAs, backlog, CSAT, escalations) to identify trends, risks, and improvement opportunities.

• Deliver clear, actionable insights to leadership and executive stakeholders.

• Develop and maintain KPI frameworks and dashboards across global regions.

• Enable performance management through data-driven insights on productivity, quality, and efficiency.

AI & Advanced Analytics

• Apply AI/ML techniques to uncover patterns and drive deeper insights at scale.

• Build models for forecasting, escalation risk, incident trends, and customer sentiment (NLP).

• Leverage generative AI to accelerate insight generation and automate reporting.

• Identify systemic issues across products, customers, and regions to enable proactive problem resolution.

Operational Improvement

• Partner with support leadership to improve SLA performance, backlog reduction, resolution times, and CSAT.

• Identify process inefficiencies and recommend data-backed improvements.

• Standardise reporting and analytics practices globally.

Data Management & Automation

• Ensure data integrity across systems (e.g., ServiceNow, CRM platforms).

• Design and maintain scalable data models, pipelines, and reporting solutions.

• Build automated and self-service analytics to enable real-time insights and reduce manual reporting.

AI-Driven Support Transformation

• Drive adoption of AI-powered analytics and decision frameworks across support operations.

• Implement use cases such as LLM-based data interrogation, NLP case analysis, and predictive analytics.

• Ensure secure, compliant, and responsible use of AI

Required Skills & Experience

Technical Skills

• 5+ years in data analytics, business intelligence, or support analytics.

• Experience in SaaS, enterprise software, or IT services environments.

• Advanced SQL and Python or R; proficiency with BI tools (Power BI, Tableau, etc.).

AI & Advanced Analytics

• Hands-on experience with AI/ML techniques (forecasting, anomaly detection, clustering, NLP).

• Familiarity with LLM tools and AI-assisted analytics workflows in enterprise settings.

Domain Expertise (Preferred)

• Experience with ServiceNow or similar platforms.

• Strong understanding of support KPIs (CSAT, SLA, backlog, MTTR, FCR).

Leadership & Communication

• Strong analytical and problem-solving capability with attention to detail.

• Ability to translate complex data into clear, executive-level insights.

• Collaborative and effective at influencing stakeholders in a global environment.

• Proven ability to drive efficiency through automation and modern analytics

Education

• Bachelor’s degree in Data Science, Computer Science, Engineering, or related field.

• AI/ML or Data Analytics certifications

Success Measures

• Improvement in CSAT, SLAs, and operational KPIs.

• Reduction in backlog, repeat issues, and preventable escalations.

• Faster, higher-quality insights through AI and automation.

• Increased adoption of self-service analytics by leadership.

• Demonstrated shift from reactive to predictive support operations