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Click here or scroll down to respond to this candidateCandidate's Name
EmploymentNeuraflash BostonAssociate Data Analyst May Street Address to July 2023 Identified 3 significant bugs in client chatbots, by SQL querying data to find inaccuracies, and by auditing the chatbots structure Communicated with stakeholders to understand their business needs, and translated this into measurable goals Aligned the priorities of my team by determining and measuring quantifiable metrics that reflect the stakeholders goals Predicted ROI of recommended enhancements of chatbots, phone IVR, or support pages to determine future projects Created dashboards and reports in Salesforce for 7+ clients, for tracking agent and team performance Led regular meetings with clients to highlight Salesforce platform performance and plan future projects Advised clients on new or improved chatbot flows to decrease escalation to agents based on NLP analysis of transcriptsBrigham and Womens The Channing Division Boston Data Engineer June 2021 to Dec. 2021 Wrote a data integration workflow python package and integrated this with a Lab Information Management System (LIMS) Built an end-to-end process for cleaning sample data, extracting PLINK analysis, using QC Jupyter Notebooks and SnakemakeWorkflows Presented QC findings in weekly meetings with bioinformaticians about analysis interpretations 1upHealth BostonData Engineer June 2020 to May 2021 Implement ETL processes to map health records to JSON FHIR records to use in customer APIs Answered client questions on patient data using SQL and Elasticsearch queries Revise Python programs to keep database interactions up to date Automated a client data mapping workflow in Apache Nifi Updated onboarding documents for a more efficient onboarding process for the next intern groupEducationNortheastern University July 2018 to May 2022BS Data Science and Biochemistry 2022Data Science ProjectsMachine Learning Exploration Python 2022 Formulated hypothesis based on data of 79 house features and the price of the house Determined a few key features to build the models using regression algorithms Performed data wrangling and cleaning in Jupyter Notebook Tested multiple ML algorithms (linear regression, lasso, ridge, and k-nearest neighbors) and used model optimization techniques to find the most accurate model to predict the price of a house Created visualizations through the data exploration and for the results Graph Database Exploration Neo4J 2021 Explored the relationship between different drugs in the UCI Drug Review Dataset and the Drug Sensitivity in Cancer Dataset using a graph database Modeled trends and provided queries to understand more about patient drug reviews regarding cancer treatments Created visualizations with findings within Neo4j ContactEMAIL AVAILABLEPHONE NUMBER AVAILABLEhttps://LINKEDIN LINK AVAILABLEradoslavov/New Canaan CTTechnical SkillsPROGRAMMING LANGUAGESPythonSQLJavaRSOFTWARE/TOOLLinuxAWSSalesforceTableauSnowflakeRedisNeo4jMongoDBPostgresSQLMySQLJupyter NotebooksGitJiraCONCEPTUAL KNOWLEDGElinear regressionclassification algorithmslogistic regressiontime series analysisdata visualizationdatabase designCertificationsSalesforce Certified BusinessAnalyst2022Salesforce Certified Administrator 2023InterestsYoga Trainer CertificationProgramSept. 2023 toPresent |
