•    Enthusiastic and self-motivated, with ability to lead projects proactively
•    Meticulous attention to detail, with an overall passion for continuous improvement
•    Innovative and creative, with a logical and methodical approach to problem solving
•    Credible and articulate, with excellent communication, presentation, and interpersonal skills
•    Ability to multi-task and manage competing priorities

• Use statistical methodologies leveraging analytical tools to support different business initiatives
• Continual enhancement of statistical techniques and their applications in solving business objectives
• Compile and analyze the results from modeling output and translate into actionable insights 
• Acquire and share deep knowledge of data utilized by the team and its business partners
• Participate in global conference calls and meetings as needed and manage multiple customer interfaces
• Execute analytics special studies and ad hoc analyses
• Evaluate new tools and technologies to improve analytical processes 
• Set own priorities and timelines to accomplish projects (accountability for project deliverables)

 Efforts will focus on the following key areas:

• Domain
• Various classical Statistical techniques such as Regression, Multivariate Analysis etc.
• Data Mining & Text Mining
• Time Series based forecasting modeling 
• Customer Segmentation – Cluster & Factor Analysis
• Customer Relationship Management Analytics
• Subscription Analytics
• Product Analytics
• Demand Modeling
• Market Research
• Statistical Scoring models to be used in Risk/Marketing domains
• Market Mix Modeling
• Structural equation modeling for identifying accelerators of customer satisfaction and loyalty
• Tech Skill
• Experience with SQL and data warehousing (e.g. GCP/Hadoop/Teradata/Oracle/DB2) 
• Experience using tools in BI, ETL, Reporting /Visualization/Dashboards 
• Programming experience in languages like Java, C, C++, with the understanding of object-oriented programming strongly desired 
• Experience with multiple Operating systems (e.g., MSDOS, Linux/Unix), and Unix scripting strongly desired
• Experience with data handling using SAS, R or Python desired. 
• Exposure to Bigdata based analytical solutions and hands-on experience with data lakes/ data cleansing/ data management.
• Soft Skill
• Good Analysis and problem-solving skills.
• Ability to get Insights from Data, provide visualization, and story-telling.
• Flexibility to explore and work with newer technologies and tools.
• Ability to learn quickly, adapt, and set direction when faced with ambiguous scenarios. 
• Excellent collaborative communication and Team skills

• Candidates should have significant hands-on experience with analytics projects using advanced Statistical / Econometrics / Operation Research / Actuarial or related quantitative techniques across various functions
• Candidates will be expected to successfully prioritize and manage multiple analytical projects / ad-hoc requests 
• Good technical depth with strong analytical/programing skills and ability to apply technical knowledge to do research
• R / SAS / Python or other quantitative analysis programming skills

Educational Qualification:

Advanced degree (Masters or PhD) in Statistics / Econometrics/ Operation Research / Actuarial Science or any other quantitative