Srishti Singh
Seattle,WA
Summary
Experienced data science professional adept at using Programming/data analysis to guide strategic decision making for industry leaders. Accomplished scientist with proven track record in data analysis and problem-solving. Developed innovative models that significantly improved decision-making processes. Highly collaborative team player, adaptable to dynamic project requirements, skilled in Python, R, and machine learning algorithms.
Overview
5
5
years of professional experience
Work History
Data Scientist
METREX
01.2019 - 07.2022
- Deployed time series forecasting model to predict foreign exchange rates, model worked as combination of 10 different ML methods (univariate + multivariate) in ensemble approach to create short-term monthly forecasts
- Generalized modelling process to 25 most important currencies in terms of USD
- Transformed foreign exchange prediction model into end-to-end ML pipeline using Airflow which can be used by clients to make better business decisions
- Created Interactive Dashboard using Dash/Plotly in Python to automate process of cleaning/inserting quarterly recommendation data feed in MySQL database which resulted in saving Annual SME time by 500 hours
- Developed analysis plans, built SKU level forecasting engine to predict future sales for every product in portfolio
- Helped save significant man hours for business insights by automating exhaustive number crunching Techniques used: Parallel computing using multi-core programming in R, ARIMA and linear regression
- Formulated Data Science strategy By Utilizing ML classification models to determine optimal recommendations of target accounts, resulting in a 7% increase in pipeline conversion rate for target accounts
- Led development of automated KPI reporting framework in Power BI for field/leader views (CEO, VPs, and Brand teams) and eliminated all manual field reporting via home office
- Automated and optimized data extraction and transformation processes using SQL and ETL tools (Synapse), resulting in 30% reduction in data processing time and 25% decrease in errors, leading to more accurate insights on real time basis
- Communicated complex business insights through effective storyboarding and data visualization tools such as Tableau and Python, enabling stakeholders to grasp key findings and make informed decisions
- Transformed results into interactive dashboards using tools like R-shiny, facilitating data-driven action plans and enhancing accessibility to insights
- Collaborated with cross-functional teams to identify relevant data sources and improve overall data quality.
- Designed experiments to validate hypotheses, leading to valuable insights into customer behavior patterns.
- Delivered actionable recommendations by conducting comprehensive exploratory data analysis on large datasets.
- Presented complex findings to non-technical stakeholders through clear visualizations and concise reports.
- Streamlined data collection methods to minimize analysis errors.
- Automated repetitive tasks using scripting languages such as Python or R, saving time during the analytical process significantly.
- Evaluated emerging technologies to assess potential applications within organization's existing infrastructure or future projects.
- Conducted feature engineering efforts to enhance model performance by creating new relevant variables from raw input data sources.
- Conducted thorough exploratory data analyses for robust model building.
- Participated actively in interdisciplinary teams'' work integrating domain knowledge from marketing, sales or finance departments into the analytical process.
- Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
- Translated business requirements into data-driven solutions, providing value-added insights that directly contributed to the organization's strategic goals.
- Pioneered use of natural language processing for analyzing customer feedback, uncovering key areas for improvement.
Data Science Intern
CashSentinel
03.2017 - 06.2017
- Developed interactive dashboards using Python, empowering sales consultants to profile customers across regions and set goals in real-time
- This initiative increased efficiency by approximately 40% and facilitated better decision-making
- Additionally, created a KPI tracker for senior leadership to monitor progress and drive strategic initiatives
- Designed marketing campaign dashboards to enable real-time monitoring of media asset performance, empowering product brand teams with insights for strategic adjustments
- Created Data Quality Management (DQM) frameworks to automate big data loading from diverse sources, cleansing, and quality check processing using a T-SQL based software
- This initiative led to a 4% reduction in runtimes, improving data accuracy and reliability while enhancing operational efficiency
Education
Master of Science - Business Analytics
Seattle University
Seattle, WA12.2024
Bachelor of Science - Computer Science
R. V. College of Engineering
India12.2019
Skills
- ANOVA
- Linear Regression
- Logistic Regression
- Random Forest
- Gradient Boosting Machine (GBM)
- Neural Networks
- Support Vector Machines (SVM)
- KNN
- Naive Bayes Classifier
- Hierarchical Clustering
- K-Means Clustering
- SQL
- Python
- Power BI
- Tableau
- Excel Dashboard
- Excel
- MS Access
- SQL server
- Azure
- AWS
- Statistical Analysis
- SQL Databases
- Machine Learning
- Sentiment Analysis
- Feature Engineering
- Data Mining
- Business Forecasting
- Anomaly Detection
Projects
Machine Learning (MS) - Airport Choice, Enhanced prediction accuracy by 13.4% through the development and deployment of classification models. Data Management for business (MS) – Data Base Design for Food delivery app, Crafted an efficient Entity-Relationship Diagram (ERD) and streamlined process flow for a food delivery app. Data Visualization (MS) – R shiny dashboard, Created to depict changes in CO2 emissions over time from 1990 to 2017 within the US.
Timeline
Data Scientist
METREX
01.2019 - 07.2022
Data Science Intern
CashSentinel
03.2017 - 06.2017
Master of Science - Business Analytics
Seattle University
Bachelor of Science - Computer Science
R. V. College of Engineering
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