Role Overview

We are seeking an experienced Exploratory Data Analyst to establish a proactive, data-driven continuous monitoring and improvement program for our Lead to Cash (LTC) workflows. You will analyze data across Salesforce, Oracle, and related systems to provide ongoing visibility into process performance, identify optimization opportunities, and monitor the impact of improvement initiatives.

Your role is to establish systematic data analytics that enable the organization to continuously enhance efficiency across sales processes, order management, billing, and revenue operations.

Your deep familiarity with LTC data domains combined with advanced data analysis skills will enable you to establish baseline performance metrics, monitor process dynamics, and proactively surface optimization opportunities. Youll apply statistical rigor and outlier analysis to uncover anomalies and performance drivers, then craft compelling data narratives and visualizations that tell the story of process performance, highlight areas for enhancement, and track the value delivered through continuous improvements.

Key Responsibilities

- Establish and maintain data extraction and preparation pipelines from Salesforce, Oracle, and related enterprise systems using Python, SQL, and data engineering tools for ongoing exploratory analysis
- Conduct regular exploratory data analysis (EDA) across LTC workflows using statistical methods and data visualization to monitor process performance and identify optimization opportunities
- Perform statistical analysis and outlier detection on LTC data to identify anomalies, performance deviations, and abnormal process patterns that signal optimization opportunities
- Define, track, and monitor key LTC performance metrics: lead-to-opportunity conversion times, quote approval cycles,



order-to-cash timelines, billing cycle times, collections performance, and process variance
- Create and maintain baseline performance benchmarks for LTC processes and establish continuous monitoring frameworks
- Build interactive dashboards and performance monitoring tools using data visualization platforms that provide real-time visibility into LTC metrics, trends, anomalies, and variance analysis
- Develop proactive, statistically-grounded data insights reports highlighting performance trends, outlier events, optimization opportunities, and areas of variance from baseline
- Create compelling data narratives and stories that communicate complex LTC performance insights: current state, performance drivers, statistical significance, and optimization opportunities
- Present findings, trends, and optimization recommendations to sales, finance, and operations stakeholders in clear, actionable formats with data-backed storytelling
- Analyze cross-functional dependencies and handoffs within LTC to understand end-to-end process dynamics, performance drivers, and variance patterns
- Collaborate with sales, order management, billing, and finance teams to validate findings and prioritize optimization initiatives by business impact
- Monitor and measure improvement outcomes post-implementation to validate the impact of optimization initiatives and inform future enhancements




- Build and maintain reusable data analysis frameworks, Python-based analytical tools, templates, and methodologies to enable scalable continuous improvement across business units

Required Qualifications & Skills

- 4+ years of experience in data analysis, business analytics, or related analytical roles
- Advanced proficiency in Python for data manipulation, analysis, and exploratory data analysis (Pandas, NumPy, SciPy, Matplotlib, Seaborn)
- Robust statistical analysis skills including descriptive statistics, hypothesis testing, distribution analysis, and anomaly/outlier detection techniques
- Hands-on familiarity with Salesforce and Oracle data structures, tables, and reporting
- Experience with Lead to Cash (LTC) domain or related business processes (sales, order management, billing)
- Advanced proficiency in SQL for querying and analyzing enterprise system data
- Strong experience with data visualization tools (Tableau, Power BI, Looker, or equivalent)
- Hands-on experience conducting exploratory data analysis (EDA) to uncover patterns, trends, and performance drivers
- Expertise in identifying and analyzing outliers, anomalies, and statistical deviations in complex datasets
- Excellent data storytelling and visualization abilitiesproven ability to translate statistical findings and complex analyses into compelling narratives for diverse audiences
- Strong communication and presentation skills—ability to explain technical findings to sales, finance, and operations audiences
- Intellectual curiosity and analytical mindset—comfort investigating performance dynamics and asking probing questions
- Ability to work independently, manage multiple analytical projects, and collaborate with cross-functional teams

📌 Exploratory Data Analyst (Bengaluru)
🏢 Allegis Global Solutions (AGS)
📍 Bengaluru