Free Data Scientist Resume Sample [2022]
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6+ years experienced data scientist with a passion to solve real-world business challenges using data analytics. Track record of setting up the Data Science Div. for a leading hospitality firm & rendering consultancy services for a Fortune 500 company. Proficient in deploying complex machine learning and statistical modeling algorithms/techniques for identifying patterns and extracting valuable insights for key stakeholders and organizational leadership.
- Packages: SciKit-Learn, NumPy, SciPy, Plot.ly, Pandas, NLTK, Beautiful Soup, Matplotlib, StatsModels
- Big Data Stack: Hadoop, Apache, Pig, Python, PostgreSQL, AWS, Hive, MongoDB, MapReduce, Spark, Linux
- Statistics/ML: Linear/Logistic Regression, SVM, Ensemble Trees, Random Forests, Clustering, Gradient Boosted trees
Data Analysis
Stakeholder Management
Leadership & Training
Strategy
Project Management & Delivery
Process Improvement
Team Incubation
Data Visualization
Predictive Modelling & Analytics
Sentiment Analysis
- Awarded the “Best Employee Award" | Positronix Financial Services, '17
- Received the 'CEO Appreciation Award' | Epiplace Solutions, '16
- Certified 'Machine Learning Expert', OpenAI, '17
- Certified 'Expert Data Scientist', Stanford University, '16
- Speaker, Open Data Science Conference, San Francisco, '16
- Published: “Modern methods of dynamic pricing for hotels”, The Data Science Journal, '15
PROFESSIONAL EXPERIENCE
Technology Stack: Python, Hadoop, AWS, Pandas, NumPy, SciKit-Learn, plot.ly
Data Visualization & Predictive Analytics
- Steering rapid model creation in Python using Pandas, NumPy, SciKit-Learn & plot.ly for data visualization
- Constituting NLP models for Sentiment Analysis & MapReduce modules for predictive analytics in Hadoop on AWS
- Unfurled ridge regression model & LASSO solver via gradient descent to select the regularization parameters
- Designing real-time contextual behavioral personalization system via econometric & ML to predict customer behavior
Statistical Modeling & ML Algorithms
- Placed various machine learning techniques to build dynamic pricing models and maximize profitability
- Led the development of a performance assessment & pricing analysis platform via k-NN Algorithm
- Formed multivariate regression based attribution models using ad stock analysis from the digital marketing data
- Generated segmentation models using K-means Clustering in order to discover new segments of users
Key Achievements
- Established the Data Science division from scratch by recruiting, on-boarding & training a team of 8 Data Analysts
- Formulated clustering & regression analysis to resolve a shipping consolidation issue & reduce costs by USD 3 million
- Successful in an overall loss reduction of 10% on monthly revenue by implementing the loss minimization techniques
- Migrated data transformation processes on Hadoop to reduce data processing time by 25% & cut costs by USD 550k
- Developed a customer segmentation algorithm using Python to boost sales leads & increase market share by 28%
Technology Stack: Python, Pandas, NumPy, SciKit-Learn, Matplotlib, Jupyter Notebook
Segmentation & Clustering
- Applied large scale & low latency machine learning for non-parametric models & high-dimensional data visualization
- Created multivariate regression-based attribution models & segmentation models using K-means Clustering
- Utilized high dimensional data sets from users/media agencies/3rd-party apps via PCA, LDA & Kernel Approximations
Key Achievements
- Developed an additive scoring model for QSM and a logistic regression model to yield a K-S statistic of 51.5
- Deployed SGD, Logistic Regression, Random Forest, SVM, etc. for classification models to boost avg. click rate by 34%
Data Analytics & Model Development
- Directed model development, validation, testing and implementation of analytical products and applications
- Developed an additive scoring model for QSM & a logistic regression model which yielded a K- S statistic of 51.5
ML Algorithms & Statistical Analysis
- Stationed advanced text mining algorithms to identify search intent latent in individual keywords
- Tested and implemented decision trees, random forests and ensemble models using bagging and boosting
- Employed Principle Component Analysis to analyze collinearity and reduce the dimensionality of the dataset
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EDUCATION
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- Languages: English, Spanish and Catalan
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Our resume experts have created this Data Scientist resume
sample after extensive research in their respective domain. You
can use the above Data Scientist resume example to directly
create your resume!
