SUMMARY

• Data Analyst and SME with 5 years of progressive experience in managing and implementing financial modeling, analysis, migrations, service management and Turn Around Time revision domains with highly developed analytical and problem - solving skills as well as an influential approach to on-shore analysts, clients, colleagues, and management.
• Now looking to make a significant contribution where extensive focus on technology, operations, and process improvement would add value to the business.
• Extensive IT experience with an in-depth understanding of Business Re-engineering, Business Continuity plan, System Architecture, Problem Solving, Strategic Partnering, Strategic Planning, Implementation, Application Design, Information Security, Data Warehousing, Business Intelligence, and Project Management.
• Experienced Data Scientist with hands-on experience in developing Machine Learning models.
• Extensive experience in the Strategic development of a Data Warehouse and in Performing Data Analysis and Data Mappings for Operational Data Stores, Enterprise Data Warehouses, Data Marts, and other databases.
• Expertise in conceptual, logical, and physical designing and development of Data Models, Data Normalization, OLTP and OLAP databases, and Data warehouses.
• Experience in diverse procedures but not limited to machine learning, deep learning, Bayesian algorithm, Regressions, cluster analysis, decision trees, time series, resampling and regularization, NLP, and other techniques.
• Strong working experience with various python libraries such as NumPy, SciPy for mathematical calculations, Pandas for data preprocessing/wrangling, Mat plot, Seaborn for data visualization, Sklearn for machine learning, Theano, TensorFlow, Keras for Deep learning and NLTK for NLP.
• Experience with common Machine Learning Algorithms like Regression, Classification, and Ensemble models.
• Experience using machine learning models such as random forest, KNN, SVM, logistic regressions and used packages such as ggplot, dpylr, lm, e1071, rpart, randomForest, nnet, tree, PROC-(pca, dtree, corr, princomp, gplot, logistic, cluster), numpy, sci-kit learn, pandas, etc., in Python.
• Expertise in applying data mining techniques and optimization techniques and proficiency in Machine Learning, Data/Text Mining, Statistical Analysis, and Predictive Modeling.
• Expertise in SQL in creating and using Views, User Defined Functions, Triggers, Indexes, Stored procedures involving joins, sub-queries from multiple tables, and established relationships between the tables using primary and foreign key constraints.
• Expert in ETL tools like Import/Export wizard and SSIS for transferring Data from different sources to a centralized SQL server.
• Hands-on experience in the Implementation of Enterprise Business Intelligence solutions using BI tools such as Tableau, Business Objects, and Crystal Reports.
• Excellent in High-Level Designing of SSIS Packages to perform ETL from heterogeneous sources such as Excel, CSV, and Text Format Data by using multiple transformations provided by SSIS to generate underlying data for the reports and to export cleansed data.
• Experience with Data analysis and SQL querying with database integrations and data warehousing for large financial organizations.
• Strong knowledge of SQL, stored procedures, data analysis, and data validation using SQL.
• Strong backgroundin Data Warehousingsystems proficient in designing and implementingSQL queriesfor reporting/data validation usingOracle, SQL Server, andDB2.
• Experienced in designing reports using SQL Server Reporting Services (SSRS) and Excel Pivot tables based on OLAP cubes.
• Extensive experience in creating and maintaining source-to-target data mapping documents.
• Documented Traceability Matrices based on defined business rules in Microsoft Excel.
• Strong documentation and analytical skills, strong problem-solving skills.
• Facilitated weekly and monthly business review meetings to keep SMEs, Stakeholders, product managers, executive staff, and team members apprised of goals, and project status, resolving issues and conflicts, and preparing product demonstrations.
• Solid business communication, and presentation skills, written correspondence, web-based products, and reports, (project status reports, PowerPoint presentations, e-mails).
• Organized, goal-oriented, self-starter, and able to master new technologies, and manage multiple tasks while following through from start to completion with limited supervision.
• Competent, confident, and strategic decision-maker organized with effective Time Management and Prioritizing skills in conflicting demands to execute business objectives.

TECHNICAL SKILLS

Languages: Python (Numpy & Pandas), SQL.

Databases: Oracle, My SQL Server.

Technologies: Tableau and Power BI for Visualization

Management/Office Tools: Microsoft Project, Microsoft Office.

Cloud Computing Platforms: Microsoft SharePoint, JIRA, Microsoft Agile DevOps.

PROFESSIONAL EXPERIENCE

Confidential, Berlin, MD

Data Analyst

Responsibilities:

• Managed multiple projects of small to large scale through sprints.
• Worked closely with stakeholders and subject matter experts to elicit and gather business requirements.
• Documented business and functional requirements, user stories, acceptance criteria, test cases, and wireframes/mockups.
• Worked directly with the Dev team to ensure product backlog was understood to the level needed and to keep sprint on the track.
• Tracked Velocity, Capacity, Burn Down Charts, and other metrics during iterations.
• Created Data flow diagrams.
• Prioritized the backlog to ensure on-time delivery.
• Used Pandas, NumPy, seaborn, SciPy, matplotlib, Scikit-learn, and NLTK in Python to develop various machine learning algorithms and utilized machine learning algorithms such as linear regression, multivariate regression, naive Bayes, Random Forests, K-means, & KNN fordataanalysis.
• Facilitated Agile team ceremonies including Daily Standup, Backlog Grooming, Sprint Review, Sprint Planning, etc...
• Assistedthe DataScientist team to Gather the Requirements, Develop Process Models, and detailed Business Policies, and modified the business requirement document.
• Performed legacy applicationdatacleansing,and dataanomaly resolution and developed a cleansing rule set for ongoing cleansing anddatasynchronization.
• Involved in project cycle plan for thedatawarehouse, sourcedataanalysis,the dataextraction process, transformation, and loading strategy designing.
• UsingPython, I have automated a process to extractdataand various document types from a website, save the documents to a specified file path, and upload documents into an excel template.
• Performeddataanalysis anddataprofiling using SQL on various source systems including Oracle and Teradata.
• Extensively used Star Schema methodologies in building and designing the logicaldatamodel into Dimensional Models.
• Maintain and enhancedatamodel with changes and furnish with definitions, notes, reference values, and checklists.
• Ran SQL queries to test and validate data in a database (SQL Server, DB2).
• Developed SQL queries /scripts to validate thedatasuch as checking duplicates, null values, and truncated values and ensuring correctdataaggregations within an ETL process testing cycle.
• Involved withdatamodel and reporting requirements for Tableau Reports with theDatawarehouse / ETL and Reporting teams.
• Worked with Users to develop Test cases for user acceptance testing.
• Drove User Acceptance Testing.
• Designed and published visually rich and intuitively interactive Tableau/Excel workbooks and dashboards for executivedecision-making.

Confidential

Data Analyst

Responsibilities:

• Analyzed and processed financial statements and performed ratio analysis to submit financial forecasting and identify potential quality concerns.
• Analyzed all the statements such as Cash Flows, Balance sheets, and Income statements of various corporate companies from the US, APAC, and EMEA regions, processed the analysis based on Confidential &P criteria, and published the accurate data accessible to customers and clients.
• Worked on quality check of the data related to the entities from all regions and suggested necessary process improvement suggestions to save manhours and attain accuracy.
• Used business objects, business intelligence, and other reporting tools to extract data from data solutions and data warehouses.
• Performed root-cause analysis on data-related system problems to recommend or execute corrective action.
• Identified, reviewed, and evaluated data management metrics to recommend ways to strengthen data across the enterprise.
• Developed and executed solutions to customer needs and drivers through hands-on engagement. Engaged in tool and process improvements to streamline customer success activities and services. Proved successful working within tight deadlines and a fast-paced atmosphere.
• Learned new skills and applied them to daily tasks to improve efficiency and productivity. Analyzed business problems, identified root causes, and developed robust solutions.
• Worked with stakeholders to develop quarterly roadmaps based on impact, effort, and test coordination.
• Utilized advanced querying, visualization, and analytics tools to analyze and process complex data sets.
• Assist other projects with data analysis, data mining, and data profiling as needed.

Confidential

Data Analyst

Responsibilities:

• Identified and documented detailed business rules and use cases based on requirements analysis. Researched and resolved issues regarding the integrity of data flow into databases.
• Documented effective and replicable methods for extracting data and organizing data sources. Developed required policies and procedures that reflected actual goals, tasks, and workflows while meeting all regulatory compliance requirements.
• Worked on a financial model with an eye for detail on key credit ratios and metrics (FFO, DEBT, EBIT, EBITDA).
• Excellent working knowledge of US and IFRS GAAPs.
• Built company A/B testing frameworks to test model quality.
• Communicated directly with project stakeholders, providing timely updates on project advancement.
• Identified staff knowledge deficiencies, scheduling educational activities to correct gaps in previous training.
• Applied DevOps practices to better integrate disparate efforts within multi-team projects. Updated operational methods and oversaw accounting procedures for improved efficiency. Contributed majorly towards automation projects, UAT testing, and adoption of lean methodologies in the existing work environment.

Confidential

Process Associate (SME)

Responsibilities:

• Work in a fast-paced agile development environment to quickly analyze, develop, and test potential use cases for the business.
• Provide regular product roadmap updates and product lifecycle management updates to customers.
• Participated in all SDLC levels of testing to provide SME validation and recommendations for corrections or improvement.
• Recommend agendas for working group meetings and conferences.
• Coordinated leadership workshops to educate team members on best practices to optimize productivity.
• Understand and work on Component Integration Testing, Interface Testing, System Integration testing, and End to End Integration Testing.
• Develop Test Plan and Strategy for Integration Testing.
• Design and Execute test cases as per the Test Plan laid out in the Test Strategy.