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Click here or scroll down to respond to this candidateCandidate's Name , MSNY Street Address PHONE NUMBER AVAILABLE EMAIL AVAILABLE LinkedIn ID: Candidate's Name
Professional SummaryExperienced Senior Data Scientist with over 5 years of experience in consulting, customer engagement and marketing strategy across industries: retail, pharma, CPG and financial services. Proven track record of managing and engineering end-to-end data science projects while collaborating with cross-functional teams. Improved data accuracy, designed complete systems, manipulated structured and unstructured data, built predictive models, and invented algorithms that identify anomalies, relationships, and trends. Strong statistical and analytical ability to evaluate, extract, and/or decode key data elements, oversee large and complex data sets, generate advanced analytical solutions, and use various skills to resolve complex issues and make technical decisions. Seeking a position as a Data Scientist (Product and AI), Machine Learning Engineer, Data Engineer to contribute to maximize revenue growth and competitiveness. Professional ExperienceSenior Data Scientist (Jan 2024 Jun 2024)Source Mantra Inc [Remote] Executed end-to-end machine learning models, regression and classification analysis for sales forecastingUsed advanced Excel and Pivot tables to analyze customer and sales data and present visualizations through PowerPoint presentations.Senior Data Analyst/ Consultant (Oct 2021- Oct 2023) Ipsos MMA [NYC, USA]Clients Serviced at MMA: Bimbo Bakeries, Sara Lee, ABO Foods, Entenmanns, Fisher Investments, JCrew, JCrew Factory, Madewell, Wrangler Jeans (Retailer and Wholesaler), O Reilly Auto, Sargento Cheese. Led a team of data analysts and scientists for marketing clients, developing predictive models to optimize marketing mix and customer segmentation, to increase campaign ROI by 20%. Utilized Python and SQL for data extraction, transformation, and analysis from diverse marketing data sources. Created marketing mix models using time series forecasting and regression analysis and evaluated these models using metrics using Advanced Excel, Pivot tables as well as programming tools including SQL, Python, AWS, Power BI, Meta and Google Suite (Ads, Analytics, Search, Social Media etc) Executed A/B tests to refine marketing strategies and improve customer engagement metrics. Collaborated with stakeholders including client marketing teams, product managers, media managers, agency leaders and engineers to elicit data and business requirements and integrate data-driven insights into marketing campaigns for each teams use. Trained stakeholders in mixed media modeling tools, techniques, and usage of KPI insights Developed dashboards to visualize key marketing performance metrics and trends. Mentored junior data scientists and provided guidance on best practices and methodologies. Monitored KPI performance, engineered ETL process and created custom queries and database finetuning using Databricks and MS SQL to analyze big data and integrate multiple data sources. Data Analyst/ Consultant (Apr 2020- Oct 2021)BlackRock [NYC, USA] Implemented Scrum and Agile methodology for efficient work management within teams. Utilized Python scripts to connect, and upload files from team sites & Excel to PostgreSQL. Demonstrated proficiency in Python libraries (NumPy, Pandas, Scikit-learn) on GitHub & implemented ML models to enhance customer targeting & personalization, with 15% sales lift. Analyzed customer feedback data to identify pain points and optimize marketing strategies. Reduced data preparation time by 40%, automating data processing pipelines using Python, SQL and Spark. Presented findings and insights to stakeholders through reports and visualizations Designed and presented interactive dashboards using Tableau and ggplot2 for stakeholders. Developed, configured, and deployed Spark applications on cluster. Created insightful data visualizations (bar charts, scatter plots, pie charts, stacked bar charts) using SQL, Python, and Jupyter. Employed R's ggplot2 package to analyze data and develop applications. Set up new EC2 instances in AWS, allocating volumes & providing Provisionals using IAM. Utilized Azure Data Factory to transfer data across VM, BLOB storage, and SQL Server. Data Analyst (Mar 2018- Mar 2019)Freelance Projects [UAE] Designed and implemented automation framework using Python and Shell scripting. Built and managed data pipelines in cloud utilizing Azure Data Factory. Utilized ggplot2 library in R to perform data analysis and generate visually appealing data visualizations for improved comprehension of customer behaviors. Conducted analysis using Python, Jupyter Notebook, and the Scientific computing stack(NumPy, SciPy, Pandas, TensorFlow, and Matplotlib). Participated in developing, configuring, and deploying Spark applications on a cluster. Developed machine learning models using R and Python. Used SQL views and SQL queries to analyze data.Clinical Skills Simulations Trainer (Jan 2017- Dec 2018) United Arab Emirates University [Abu Dhabi, UAE] Trained Year 4 medical students in clinical skills and simulations exercises at the university. Experiential LearningNortheastern University Industry Partners (2020) General Electric Aviation: Created a Risk Analytics framework and model to reduce false positives using CRISP DM Methodology on KNIME platform. Saved the company millions of dollars and reduced the chances of intellectual property theft by significantly reducing false positives previously obtained by a dynamic risk alert system. Used advanced data science and machine learning methodology to validate and test the model. Practera Inc: Successfully programmed using machine learning libraries in Python to conduct experiments and answer ad hoc questions on correlations between student performance, teachers and the learning platform performance, enhancing data management and platform enhancement strategies.Education MS Computer Science, Monroe College, 2024-Ongoing (US) MS Data Modeling, Warehousing, Administration, Northeastern Uni, 2019-2020 (US) Bachelors in Business Administration, IBA, 2009-2013Skills Programming Languages: Python, SQL, R, C++ Machine Learning Engineering: Pandas, Numpy, API, Scikit-learn, TensorFlow, PyTorch. Algorithms: Forecasting, Clustering, Classification, Reinforcement learning, Deep Learning, Neural Networks, Gradient Boosting, Feature Engineering. Model Interpretation & Validation: MAPE, Rsq, Adj Rsq, MSE, Kfold Cross Validation. Artificial Intelligence: LLM, RAG, LLAMA Data Visualization: Tableau, Matplotlib, Seaborn, Power BI Big Data Engineering: Hadoop, Spark, GCP BigQuery. Hive Marketing Analytics: Customer Segmentation, Marketing Mix Modeling, A/B Testing. Soft Skills: Analytical Thinking, Problem-Solving, Communication, Team Collaboration Methodologies & IDEs: SDLC, Agile, Waterfall, Visual Studio, PyCharm Cloud Technologies: AWS (S3, EC2, IAM, DynamoDB), Azure Architecture, Snowflake, System Resources: SQL Server, Cloud Computing, Distributed Computing Academic Projects (public datasets) Sentiment Analysis on Social Media Data: Used Python & NLP, achieved 75% accuracy. Sales Forecasting Model for Retail Sales: Utilized Prophet & ARIMA, R-sq 0.68. Recommendation System: Built with collaborative filtering using Python and Scikit-learn to suggest products to users based on their browsing history, with 90% accuracy. Customer Churn Prediction: Used logistic regression, decision trees, improving retention. Image Classification using CNN: Designed and trained a convolutional neural network (CNN) to classify images into various categories with an accuracy of 86%. Natural Language Processing (NLP) for Text Mining Classification: Document management Fraud Detection System: Utilized anomaly detection techniques on financial transactions. Market Basket Analysis: Used association rule mining to identify product pairs frequently purchased together, aiding in cross-selling strategies. Customer Segmentation: Applied clustering algorithms to segment customers based on purchasing behavior, providing insights for targeted marketing campaigns. A/B Testing for Marketing Optimization: Designed/ executed A/B tests to evaluate the impact of different marketing strategies on customer engagement and conversion rates. Loan Performance and Default: Used logistic Regression, and Statistical Analysis for dataset analysis, achieved 78% accuracy Website Design: Created a personal website landing page using HTML, CSS & Javascript. |
