Technology Analyst Resume

PROFESSIONAL SUMMARY:

Certified SAS programmer with over 5 years of experience in analysis, design, development, testing and validating the applications.
Experience in creating visually impactful dashboards using Qlikview, Tableau and R. Also understand big - data technology such as Hadoop.
Passionate about finding insights in data. Experience in using advanced statistics and complex SQL queries to answer business questions.
Experience in developing database ETL environments with business intelligence applications such as Microsoft SQL, Informatica and SSIS.
Expertise in developing front office trading applications and providing real time market analysis reports to traders and Risk Management team.

TECHNICAL SKILLS:

TECHNICAL: R,SAS/BASE, SAS/STAT, SAS/Macro, SQL, Java, Unix, Python

FUNCTIONAL: Data Visualization, Machine Learning, Data Warehousing, Data Modelling, Statistics, Data Structures, Database Management, Risk Management, Hadoop/Hive/Spark, VBA

TOOLS: SQL Server, Oracle, Sharepoint, Qlikview, Microsoft Access, Excel, SAS Enterprise Miner, SAS 9, Tableau, SSIS, SSAS

DOMAIN: Finance-Equity Derivatives, Life Science-Pharmaceutical

PROFESSIONAL EXPERIENCE:

Confidential

Technology Analyst

Responsibilities:

Interact with traders and Risk Managers regularly to develop design and integrate technology solutions which enable them to gather, organize and analyse high volumes of unstructured data.
Develop suite of applications consisting of Strategies pricing and booking tool, Risk and PnL scenario analysis tool and volatility spreads viewer.
Determine important KPIs for Sales Team and communicate them pictorially through reports and dashboards
Create automated tools for comparing reports, thus reducing error rate by 25%.
Build automated framework for generating reports including statistical metrics delivering concise and actionable information to traders.

Confidential

Systems Engineer Business Intelligence and Data Analytics

Responsibilities:

Collaborated with Directors of one of the world’s largest pharmaceutical firms to gather business requirements and manage clinical data.
Executed qualitative and quantitative data analysis using SAS and R, determined risk adjustment strategies and presented results across several teams and managers in Confidential
Extracted and analysed structured and unstructured data to identify trends and relationships, enabling client make effective strategic decisions.
Designed and developed transformation rules to generate consolidated data using Informatica ETL load.
Designed and Implemented machine learning models to predict useful information about patients of clinical trials.
Conferred “STAR OF THE MONTH” for predicting the most effective medicine for children suffering from pneumococcal pneumonia
Mentored and supervised the work of seven other team members and, conceptualized and implemented trainings at project level.
Conducted trainings on extraction of useful information from big data using advanced statistics and ETL tools such as Informatica.
Enhanced problem-solving skills by evaluating process in assignments, hence reducing the team’s workload by 15%.

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