Sas Programmer Data Analyst

SATYA ANGADALA

SUMMARY:

More than ** years of programming, analyzing and data gathering experience in the design, implementation, customization and development of state-of-the-art software in the field of clinical information and database management systems to suit the needs of the different business clients. SAS certified professional with experience in analyzing and coordinating clinical trial data, healthcare data, generating reports, tables, listings and graphs using SAS / SQL in accordance with the Statistical Analysis Plan (SAP), Standard Operating Procedures (SOPs) and departmental guidelines.

SKILLS:

Strong experience on Base SAS and MS SQL, SAS/Stat, SAS/Access, SAS/Graphs and SAS/Macros, SSIS and SAS/SQL in UNIX and Windows Environment.

Data Validation and Data cleansing on Clinical Trial data using Statistical procedures like PROC FREQ, PROC MEANS, and PROC UNIVARIATE.

Generate reports using PROC REPORT, DATA_NULL_ and PROC TABULATE.

Expertise in Data archival and Data migration, ad-hoc reporting and code utilizing SAS on UNIX and Windows Environments.

Expertise in producing RTF, PDF, HTML files using SAS ODS facility.

Create Analysis Datasets, Summary Tables, Listings and Plots according to the specification of the study for statistical analysis.

Worked on Transact-SQL (DDL, DML, DCL) and in Design and Normalization of the database tables.

Experience in implementing business logic using SQL Triggers, Indexes, Views and Stored procedures.

Extensive Knowledge of advance query concepts (e.g. group by, having clause, union so on).

Experience with tools like SQL Server management studio and SQL Server 2005/2008 integration (SSIS) and reporting services (SSRS).

Proficient in Tuning SQL queries to improve the database performance and availability.

Good knowledge in Normalizing and De-normalizing the tables and maintaining Referential Integrity by using Triggers, Primary and Foreign Keys.

Expertise in creating Packages using SQL Server Integration Services (SSIS).

Familiar with the clinical data reporting in CDISC SDTM 3.1.2 format

Familiar with CDISC conventions i.e., SDTM and ADAM models and hands on experience implementing them.

Experience working with Oncology data and grading solid tumors using RECIST and CTCAE criteria.

Accustomed to working in challenging environments under deadlines, excellent analytical, and problem-solving skills

TECHNICAL SKILLS:

SQL TOOLS: SQL Server, Oracle, Sybase, Access, SQL, PL/SQL MS-OFFICE, WORD, EXCEL, POWERPOINT, ACCESS, PROJECT

SAS Tools: SAS 8/9/9.4, SAS/GRAPH, SAS/STAT, SAS/REPORT, SAS/ODS, SAS VIEWER, SAS LOG CHECKER

Analytics Languages: SAS, SQL, R and Python

Databases: Microsoft SQL, Hadoop, Oracle, Salesforce and My SQL

Environment: Unix, Linux, Windows

WORK EXPERIENCE:

July 2021 – Current

IQVIA – (JACCH NON-J&J )

Senior Statistical Programmer

Generated draft and final sets of summary data tables and analyses as part of oncology clinical study reports.

Worked on SPACE cloud tool and developed utility SAS macros for use in project programs.

Wrote project-specific programming code to produce summary data tables and analyses, as specified in statistical analysis plans.

Produce tables and analyses for all reporting events for all data including PK concentration parameters.

Validated SAS macros and derived data sets developed by other programmers.

May 2019 – July 2021

University of Massachusetts (UMASS) Medical School

Biostatistician III

• Conduct claims analyses using Massachusetts Medicaid data to support various research and evaluation projects by using SAS and Python tools.

• Analyze quantitative data that will be needed for evaluation to support the Massachusetts Medicaid 1115 Demonstration Evaluation.

• Advance knowledge of Clinical Data analysis and Quality measures by using analytical tools to summarize data in a meaningful and presentable format.

• Evaluate and calculated number of opioid overdose deaths in Massachusetts that are similar to 23 states in their Medicaid eligibility criteria.

• Use technical skills to schedule reports and to produce user requested data templates/reports for user self-service reporting.

• Used knowledge of Software Development Lifecycle Cycle (SDLC) Management, maintain responsibility for all Requirements Gathering, Effort Estimation for Design, Development Testing and Implementation and Maintenance.

• Worked on 1115 wavier project with goals to improve quality and establishing greater control over spending.

• Validate and Analyze data using modelling and complex algorithms in SAS / SQL programming.

• Create matrix for Physician performance profiling like Re-admission rate, mortality, length of stay etc. by using python.

• Understand, apply and present mathematical, quantitative and statistical concepts like Quantitative and Qualitative data to support evidence-based decisions and drive change.

Mar 2016 – May 2019

Conifer Health Solutions

Clinical Data Analyst

Advanced knowledge of CI Clinical Data analysis and Quality measures by using analytical tools to summarize data in a meaningful and presentable format.

Worked with different cross functional teams internal and external dealing with different kinds of claims like CI, PMPM (per member/per month), Capitation and fee-for-service (FFS) and IBNR (incurred but not received).

Worked closely with Data Management team for processing data from different hospitals and markets like (LA care, San Antonio) by using OMOP common model.

Using technical skills to schedule reports and to produce user requested data templates/reports for user self-service reporting.

Worked on FDI project basically converting the SAS code to SQL code for ACO Medicare and Medicaid services (CMS).

Used SAS Reports, SQL, Excel and Access to perform the functions of data extraction and reporting.

Coordinated with health care professionals for avoiding data errors in EPIC EHR (Electronic Health Records).

Wrote Stored Procedures to optimize queries and make reporting faster.

Developed reports in the most efficient manner to process data for delivery to internal and external customers.

Used both automated report generation and manual ad-hoc to extract and report data in either requested template formats or a user-friendly readable format.

Jan 2012 – Mar 2016

Gilead Sciences

SAS Clinical Programmer

Utilized SAS Macros to develop tables, listings and figures. Extensively used PROC Reports to create listings and PROC graphs to create figures. Used SQL to convert Clindex data into SAS and for data manipulation.

Involved in Statistical programming and validation of Analysis Datasets and Tables, Listings, Graphs (TLG'S).

Generated the ADaM models from the CDISC SDTM baseline with data attributes such as structure, content and metadata that are typically found in clinical trial analysis datasets.

Worked on with different phases of Oncology clinical trials like Phase 1 and Phase2.

Created Patient narratives and generated .XML outputs for FDA regulatory submissions.

Worked closely with team Statistician and prepared Adhoc reports for analysis.

Created edit check programs to find data discrepancies in raw datasets.

Programed customized data displays, (including data listings, summary tables and routine graphics) in accordance with approved statistical analysis plan and shell displays for clinical research studies.

Successfully processed extremely large volumes of data into manageable SAS datasets for storage in an Oracle data warehouse.

Developed and analyzed clinical data as well as programming SAS codes to meet company and client standards.

June 2007 – Jan 2012

Kalobios Pharmaceuticals

SAS Programmer

Analyzed data using SAS Statistical Procedures such as Proc Means, Proc Tabulate, Proc Freq, Proc Summary.

Created the Study Data Tabulation Model (SDTM) baseline flag for specific visit or the last non missing result prior to first dose based on team consent.

Created the analysis data sets by manipulating the data according to the specifications and annotated the Case report forms.

Generated listings and tables using PROC REPORT and PROC TABULATE, PROC FREQ AND PROC UNIVARIATE.

Generated Summary tables and developed different types of statistical reports.

Extensively used company standard macros for effective and efficient outputs for clinical trials. Created study specific macros for better performance.

Served as lead validator in clinical team environment: created and maintained validation notebook, participated in quality assurance (QA) charts and data review, interacted with team members and company clients, validated tracking forms and collected documentation from all support programmers. Responsibility also included validating work performed by others as well as analyzing team-programming plans.

Prepared documentation with all datasets and variables within, including derived variables, and the project as whole.

Validating the datasets and comparing the results to that of source programmers’ output.

Quickly gained a detailed understanding of the Protocol, Annotated CRF, Controlled Terminology, and raw datasets (extracted from the CDMS) for all studies assigned.

Keeping abreast of Protocol Amendments, updates to Annotated CRFs, updates to Controlled Terminology, and changes to Study Design impacting the raw datasets – address all changes that have an impact on the development of the SDTM in a timely manner – keep all Parties informed of these changes via the Issue Log and follow-up with an email to ensure that everybody is aware of the impending change.

oDescriptive Analytics:

Summarize and visualize the data to understand characteristics of data.

The data has been rigorously massaged and thus the characteristics of the data have been studied.

Derive visual and tabular summarization insights for an easy understanding using data scientist tools.

oDiagnostics:

Each data element studied carefully for hidden patterns

Multiple Predictive statistical algorithms used to unveil the impacting parameters which are most sensitive to be faulty.

Built in models has been validated for its accuracy and further used Solution development.

oPrognostics:

Developed an end-to-end methodology to predict failures by analyzing patterns in historic data

Successful in deploying the Solution in Productive environment.

Environment: SAS 8/9, SAS/BASE, SAS/MACROS, SAS/ACCESS, SAS/SQL, SQL, Oracle, SAS/ODS, Excel/Access 2000, UNIX

EDUCATION:

Master’s in Computer Science, San Jose State

Bachelor’s in Engineering, University of Mumbai, India

CERTIFICATIONS:

SAS BASE Programming certification.

Developing Microsoft SQL Server Databases – 464 ( -MS0989813296)

COURSES ATTENDED:

Introduction to statistics: Descriptive statistics-The University of California, Berkeley.

Health in Numbers: Quantitative Methods in Clinical & Public Health Research Stanford CA

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