Arkatechture

Data Analyst

• Design, develop, and maintain advanced analytics solutions, including predictive models and Generative AI applications, using SQL, Python, and modern AI and BI tools
• Translate business problems into data-driven and AI-enabled solutions
• Responsible for end-to-end delivery of analytics and AI initiatives, from data exploration and feature engineering to model development, deployment, and ongoing optimization
• Design and engineer features from diverse data sources, including first-party and third-party data, to improve model accuracy and business relevance
• Operationalize models using robust MLOps practices, including deployment pipelines, automated scoring, version control, and scalable data integrations
• Define, monitor, and continuously improve model performance using appropriate metrics, including validation frameworks, drift detection, and retraining strategies
• Translate model outputs into scalable, user-friendly analytics products and dashboards (e.g., segmentation, propensity scores, next best product recommendations) for end-user consumption
• Design and evaluate experiments, including A B testing, to measure model effectiveness and quantify business impact
• Integrate AI, machine learning, and Generative AI capabilities into analytics workflows and product solutions
• Champion the adoption of Generative AI across teams by identifying and implementing use cases that improve productivity, insight generation, and client value
• Explore and implement solutions leveraging LLMs, prompt engineering, and AI-assisted analytics
• Educate and enable internal teams on AI and Generative AI best practices through documentation, training, and reusable frameworks
• Collaborate with Product, Engineering, and Services teams to evolve the Analytics Edge and AI roadmap
• Troubleshoot complex data, model, and system issues, identifying root causes and implementing scalable solutions
• Communicate insights, risks, and progress clearly to stakeholders, including both technical and non-technical audiences
• Create and maintain comprehensive technical documentation for data models, AI workflows, and processes
• Participate in Agile and Scrum ceremonies and contribute to continuous improvement of team processes
• Support client-facing discussions, demos, and training sessions as needed

Senior Data Analyst

Analyst

• Lead and support the Data and Analytics Support Desk function, providing both technical leadership and day-to-day guidance to analysts and team members
• Act as a player-coach, maintaining hands-on involvement in complex support cases while mentoring and developing the team
• Serve as a senior escalation point for advanced SQL, ETL/ELT, data warehouse, and BI-related issues
• Drive high-quality resolution of complex data platform issues, ensuring strong technical standards across all work
• Coach and mentor team members to deepen technical expertise, improve troubleshooting approaches, and grow professionally
• Own prioritization and triage of high-impact incidents, ensuring efficient routing and resolution
• Drive SLA adherence while maintaining a high bar for technical accuracy and quality
• Conduct root cause analysis (RCA) on recurring data defects and partner with Engineering and Product on structural improvements
• Ensure clear, proactive, and technically sound communication with clients throughout issue resolution
• Partner cross-functionally with Engineering, Product, and Customer Success to address systemic platform issues
• Identify trends, risks, and opportunities to improve platform performance, reliability, and scalability. Partner with the Head of Support Services to implement structural improvements and elevate service quality.
• Contribute to documentation, best practices, and knowledge sharing to reduce recurring issues
• Support operational tooling (PagerDuty, Jira, etc.) to ensure effective incident management and reporting
• Participate in hiring, onboarding, workforce planning, and performance management.
• Additional responsibilities as assigned.

Lead Analyst, Data & Analytics

Customer Success Manager

• Drive Customer Success outcomes by owning, managing, and growing overall customer health and value across our Arkalytics accounts
• Build trusted relationships with customer stakeholders and develop a deep understanding of customer goals and strategic initiatives
• Lead quarterly business reviews and strategic planning sessions with customers
• Influence long-term customer value through increased product adoption, customer satisfaction, and overall account health
• Identify, log and communicate risks and opportunities within accounts through customer engagement, product adoption, and feedback
• Act as a trusted advisor to customers by helping them align Arkalytics with their organizational goals
• Lead and support a small team of Customer Success Managers through mentorship, coaching, and ongoing development
• Serve as a resource and escalation point for complex customer situations
• Help establish and refine Customer Success processes, playbooks, and best practices
• Set team goals and monitor performance to ensure consistent, high-quality customer engagement
• Foster a collaborative and customer-centric culture across the Customer Success team
• Work closely and cross-functionally with Implementation, Product, Service Delivery, Marketing, and Sales teams to ensure a seamless customer experience
• Aggregate customer feedback and insights to help inform product improvements and roadmap discussions
• Collaborate with internal teams to resolve customer issues and ensure timely responses to requests and service needs
• Provide strategic input on customer success programs, onboarding approaches, and ongoing customer engagement strategies
• Help ensure customers are receiving strong support and service throughout their lifecycle with Arkatechture

Head of Customer Success

Manager

• Lead and oversee the Data and Analytics Support Desk function, managing analysts, engineers, technical account managers, and ArkaIndia technical analysts to ensure high quality resolution of complex BI and data platform issues.
• Maintain hands-on involvement in support cases, directly contributing to ticket resolution where technical depth or escalation expertise is required. Operates as a player coach.
• Manage, mentor, and coach team members, fostering continuous learning, technical depth, accountability, and professional growth.
• Own prioritization and triage of support issues, with emphasis on high impact data, BI, and platform related incidents. Ensure complex tickets are routed appropriately and resolved with urgency.
• Drive SLA adherence while maintaining strong technical standards across SQL troubleshooting, dashboard enhancement and validation, data model integrity, ELT/ETL pipeline reliability, and platform performance.
• Serve as the highest level technical escalation point for complex data warehouse and analytics platform issues. Diagnose and remove technical blockers to accelerate resolution.
• Ensure clear, proactive, and technically sound communication with clients at all stages of issue management.
• Oversee operational tooling including PagerDuty, Smartsheet, Jira Service Desk, and NetSuite to ensure effective incident management, tracking, and reporting.
• Develop and enhance customer facing support resources such as FAQs, known issues documentation, and BI best practices to reduce recurring defects and improve platform stability.
• Lead cross functional technical reviews with Engineering, Product, and Customer Success to address systemic data issues, platform defects, and performance trends.
• Identify risks, recurring patterns, and opportunities for process optimization. Partner with the Head of Support Services to implement structural improvements and elevate service quality.
• Act as a trusted technical advisor to internal teams and customers on BI architecture, data integrity, and analytics platform best practices.
• Participate in hiring, onboarding, workforce planning, and performance management.
• Additional responsibilities as assigned.

Senior Data Analyst

Lead Analyst, Data & Analytics

Head of Customer Success

Manager, Analytics Platform Support