SUMMARY:

• As a data scientist, looking for leading role in the organization to understand data, analyse it, set standards, derive insights and use them effectively to help customers use the platform and improve business. Forward thinking and visionary leadership to achieve corporate objectives and vision with special focus on solving complex business problems in healthcare, finance retail and insurance industries.
• 15+ years of Working Professional Experience in data modeling, statistical modeling, machine learning and data mining using SAS, R, SQL and MS Access.
• 8+ years professional working experience with consumer credit risk modeling and risk profiling using R, Visual Basic and Tableau.
• 5+ years working with different types of data sets - structured and unstructured data using Hadoop and spark R.
• Excellent communication developed during professional work both written and oral, with the ability to effectively communicate results to diverse audiences and stakeholders internally and externally.
• Demonstrated agile and analytics mind, a mindset of collaboration, acreative thinker and confidenceto operate at the highest-level client focus with ease in achieving strategic and actionable results for top fortune 500 company.
• A pride in excellence, an ability to inspire and galvanise multi-skilled teams, entrepreneurial instinct and mentor and takes ownership working for Commonwealth Bank.
• Executional Leadership: Demonstrated ability and drive change and build new capabilities / functions. Ability to manage the complexity of multiple products and services simultaneously.
• Work Style: Works collaboratively across expertise areas and functions; seeks to advance higher goals; highly regarded across stakeholders both at senior and junior levels; inspires trust at all levels.
• Specialities: Data Strategy, statistical tools, Data mining using machine learning.

TECHNICAL SKILLS:

• SAS Enterprise Miner, R, Visual Basic, MS Access, Excel, Stata 14, SPSS, GIS, Mapinfo, Tableau.
• Databases: SQL Server, Oracle, DB2, Sybase, Big Data
• Microsoft Azure, Hadoop, Spark R
• Big data including large unstructured and structured data, data strategy, traditional and advanced statistical & analytics tools, text mining, AI & machine Learning, predictive analytics, campaign analysis and strategy, spatial visualization & reporting in cloud computing environment.
• Research analysis, Econometrics modeling, forecasting, market intelligence analysis, credit risk modeling.

PROFESSIONAL EXPERIENCE:

Confidential

Senior Data Scientist

Responsibilities:

• Worked on Microsoft Azure Environment using predictive modeling for credit cards and loan portfolios.
• Developed and collaborated with other team members to design campaign strategies to increase sales and revenues using Azure environment
• Implemented Industry best practice protocol and business processes to ensure data integrity and data management for internal and external compliance.
• Assessing impact of pricing on key profit drivers and performance metrics and developed robust pricing model.
• Prepared monthly dashboard updates for products using access and tableau across business functions for visualization.

Environment: Microsoft Azure, SAS Enterprises, Machine Learning, Macros SQL, R, MS Access, Excel, Visual Basic, and Teradata

Confidential

Data Scientist

Responsibilities:

• Prepared Data strategy and market intelligence analysis developed communication with census data,
• Developed various scenarios and effect of each factor on the model outcome.
• Constructed LDA, PCA, propensity model, survival analysis and effect of each factor on the outcome model to compare 2 groups and formulated statistical hypothesis.

Environment: Microsoft Azure, Machine Learning, Statistical techniques, Hadoop, MapReduce

Senior Data Scientist

Confidential

Responsibility:

• Integrate data sources, develop, validate, and productionize machine-learning algorithms pertaining to route planning and optimization, along with various algorithm techniques.
• Mine and organize data sets of both structured and unstructured data.
• Built efficient, flexible, extensible, and scalable solutions for big data handling.
• Develop interactive dashboards and reports

Environment: Microsoft Azure, Big Data, Server R, SQL, MS Access, Excel, Visual Basic

Confidential

Senior Data Scientist

Responsibilities:

• Constructed predictive modeling for Loan Portfolio profile.
• Developed credit scoring to support automated credit assessment and risk-based pricing strategies.
• Present findings and recommendations to stakeholders to improve the overall credit risk management framework and strategy.
• Developed complex SAS Macros to simplify SAS code and effectively reduce coding time, cost and increase productivity.
• Built segmentations utilizing both internal bank behavioural scores and external bureau attributes to differentiate customer base.
• Sensitivity analysis - if lower/increase risk criteria/score cuts, what will be the impact to the P&L, pre/post treatment analysis, cohort analytics

Environment: SQL, SAS Enterprises, MS Access, Excel, Visual Basic

Confidential

Senior Statistician/Data Manager

Responsibilities:

• Construction of clinical data warehouse and maintenance/update clinical trial patients.
• Used SAS Enterprise Guide to access clinical data, import in SAS format, build predictive modelling, and produced regular reports.
• Prepared survey data to collect simple information for health patients
• Predictive modeling using longitudinal data to monitor HIC health patients and reporting.
• Sample size calculation, writing statistical analysis plan, writing stats part of protocol, performing randomization and hypothetical testing.
• Expertise in design and analysis of all areas of clinical development from basic R&D through translational science, and all phases of global clinical trials, dealing with global regulatory agencies including TGA, PBAC and FDA.
• Led team to FDA, USA

Environment: SQL, SAS Enterprises, R, MS Access, Excel, Visual Basic, Teradata

Confidential

Senior StatisticianAugust 2003-June 2006

Responsibilities:

• As Senior Statistician, responsible for statistical design and methodology for all clinical and consulting projects globally.
• Providing expert statistical advice in all areas of drug development, manufacturing, compliance meetings with clients and regulatory agencies, undertaking design and analysis of non-clinical and clinical studies as well as meta-analyses in accordance with applicable regulatory guidelines.
• Mentored biometrics staff on statistical theory and methodology. Advised clients and internal staff on statistical and associated regulatory considerations during the planning of drug development programmes across all disciplines;
• Review preclinical, pharmacological, clinical data, and statistical analysis methodology, in support of Clinical Research and Regulatory Affairs Consulting projects.
• Responsible for statistical support to translational science, Pharmacovigilence, Pharmokinetics, R&D, and Product development.
• Prepare randomization specifications; generate schedules; verify randomization components (specification and schedule). Provide input into planning activities related to the preparation of, distribution of and access to randomization and unblinding information.
• Independent peer review of statistical deliverables, e.g., protocols, Statistical Analysis Plans, Tables, Figures and Patient Data Listings, statistical reports and Clinical Study Reports.

Environment: SQL, Statistical and predicting modelling, time series analysis, internal and external compliance, operating procedures, SAS, MS Access, Excel, Visual Basic, ArcGIS, Sybase

Confidential

Senior Data Analytics

Responsibilities:

• Prepared Ad-hoc queries, and collaborating with internal and external team members from across functions.
• Prepared fire risk map for residential, commercial and bushfire (wildfire) areas using GIS for efficient operational purpose.
• Prepared credit risk profile for customers who lost/damaged properties and car accidents using SQL and SAS software.
• Provided monthly, quarterly and yearly report derived from statistical analysis for budgeting and resource allocations purpose.
• Developed software tools by combining SQL, VB.Net, access, excel and SAS to produce automated reports on timely basis.
• Integrating organizational, government, people and sensor data for modeling bushfires, outcome and reporting.

Environment: SQL, SAS, MS Access, Excel, Visual Basic, ArcGIS, Sybase