Free Data Scientist Resume Sample [2020]

Average Resume Rating: 4.8/5 (42 votes)

Updated on: 2022-10-10

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

Enter text here..

EDUCATION

Enter text here..

Languages: English, Spanish and Catalan

Our resume experts have created this data scientist resume sample after extensive research in the data science domain. You can use the above data scientist resume example to directly create your resume!

Use this Data Scientist
Resume Sample to

Create Your Resume Now!

Free Data Scientist Resume Sample [2020]

Data Analysis

Stakeholder Management

Leadership & Training

Strategy

Project Management & Delivery

Process Improvement

Team Incubation

Data Visualization

Predictive Modelling & Analytics

Sentiment Analysis

Use this Data Scientist Resume Sample to

Use this Data Scientist
Resume Sample to