Data Scientist Resume Samples

Description :

1. Assisted in determining client needs, deliverable design, estimates, and feasibility for analytical projects concerning a custom study for a manufacturer who is using the results to support a litigation claim.
2. Served as an internal resource for Jackknife programming and documentation.
3. Designed and developed small scale deliverables related to the custom study.
4. Participated in the Post Project Review QIP team.
5. Responsible for results reporting in the appropriate media and creation of supporting documentation for the client.
6. Monitored products from statistical programs for accuracy, consistency, and statistical validity.
7. Designed and applied statistical and mathematical methods for corporate analytics that were implemented into client-facing products.

Experience

10+ Years

Level

Senior

Education

Bachelor Of Science

Description :

1. Real-Time Trend Detection First non-founder employee.
2. Developed and established the Intelligent Playground of Bottlenose from the ground up.
3. Used weighted SVM on top of signal processing techniques to find trends in social-media before competitors.
4. Found breaking-news significantly sooner than news agencies on over 80% of occasions.
5. Developed patented methods of correlation on streaming data.
6. Combined noise-deduction with different correlation metrics to detect time-lag relationship between thousands of live social-media data metrics.
7. Built trend detection and correlation finder to detect abnormal behaviour of log data, identifying fraudulent activity in the cyber security space.

Experience

5-7 Years

Level

Executive

Education

PhD In Statistics

Description :

1. Analyzed MTA subway data and New York City census data to determine traffic flows and demographic patterns of New York City.
2. Used Beautiful Soup to scrape publicly available movie data to better understand the relationship between box office performance and distribution company.
3. Used sci-kit learn, ran linear regression, and built a model of box office performance.
4. Based on the model, identified two distribution companies whose revenue outperformed peers.
5. Setup SQL database on a cloud server, storing client's data for query analysis.
6. Used Python's sci-kit-learn library to understand the details of a client telemarketing campaign.
7. Used machine learning algorithms to build a model able to predict which clients to engage based on a variety of client, macro, and campaign-specific characteristics.

Experience

2-5 Years

Level

Executive

Education

Diploma In Chinese Mandarin

Description :

1. Used matplotlib and reveal.js to communicate the results of research.
2. Attended scientific conferences and teleconferences to help market, promote, and demonstrate company products.
3. Ensured on-time execution and implementation of sales planning analysis and reporting objectives.
4. Cross-platform software development on Linux, Windows, Mac Extensive experience in graph theory applications, relational databases, and multi-threaded code.
5. Reinvented the way sales forces operate, equipping them with data-driven tools to support the prioritization of their efforts.
6. Optimized the pricing of products in real-time.
7. Optimized marketing spend allocation across channels.

Experience

2-5 Years

Level

Executive

Education

GED

Description :

1. Business Opportunity Network Kinetix provides Business Assurance and Revenue solutions to mobile carriers, enabling non-intrusive access to 'live' network traffic for immediate analysis, decisions, and action on revenue-impacting events.
2. Examples include Fraud Detection (International Revenue Sharing Fraud, Identity Fraud, SIM Box By-Pass Fraud), 911 Outage, Network Operations, and Customer Experience.
3. Contributed Model complex mobile carrier problems through using statistical, algorithmic, mining, and visualization techniques.
4. Produced operable insights using supervised and unsupervised machine learning.
5. Integrated live data from multiple network protocols.
6. Created live data analytics applications that make data-driven decisions on each event as it enters the data pipeline based on rules discovered through machine learning.
7. Deployed on the HP Helion Public Cloud demonstrating a scalable cloud version of network data analytics application.

Experience

2-5 Years

Level

Executive

Education

Bachelor's In Mathematics

Description :

1. Worked closely with various teams across the company to identify and solve business challenges utilizing large structured, semi-structured, and unstructured data in a distributed processing environment.
2. Analyzed large datasets to provide strategic direction to the company.
3. Performed quantitative analysis of product sales trends to recommend pricing decisions.
4. Conducted cost and benefit analysis of new ideas.
5. Scrutinized and tracked customer behavior to identify trends and unmet needs.
6. Developed statistical models to forecast inventory and procurement cycles.
7. Assisted in developing internal tools for data analysis.

Experience

2-5 Years

Level

Junior

Education

MSc In Engineering

Description :

1. Data Mining, Modeling, and Algorithm Development Implemented novel algorithms for modeling chemical systems and mining chemical databases using the extensive application of graph theory.
2. Algorithms include confirmation sampling, drug design, and reaction-based design through graph manipulations.
3. Conceptualized and designed a hierarchical database enabling fast graph isomorphism searches for storing and retrieving chemical information.
4. Software Development Experienced in developing object-oriented code in a team environment using software design patterns, revision control, and unit testing.
5. Predictive Modeled, and Statistical Analysis Using artificial neural networks (ANN) for correlating chemical structure to drug-likeness of molecules.
6. Identified novel molecules with activity against a cancer-causing protein target.
7. Developed novel ANN algorithms for improving the prediction of drug-likeness of molecules that occur in multiple states by modifications to back-propagation and weight update schemes.

Experience

7-10 Years

Level

Consultant

Education

PhD In Computational Chemistry

Description :

1. Focused the project was on sales prediction by using sales data into a supervised classification algorithm to predict customer churn and implement a successful strategy.
2. Supported sales forecasting & planning team by improving time series & principal component analysis.
3. Utilized machine learning techniques for predictions & forecasting based on Sales training data.
4. Executed overall data aggregation/alignment & process improvement reporting within the sales dept.
5. Managed Data quality & integrity using skills in Data Warehousing, Databases & ETL.
6. Monitored and maintained high levels of data analytic quality, accuracy, and process consistency.
7. Assisted sales management in data modeling.

Experience

2-5 Years

Level

Junior

Education

Diploma

Description :

1. Performed data extraction, transformation, and loading (ETL) development and programming.
2. Performed data mining, data analysis, and performance measurements on business-information systems by using analytics tools and methodologies.
3. Carried out Marketing Analytics (Basel II), Risk Management (Logistic regression), and Survival Analysis to evaluate customer information.
4. Worked on importing data from various sources and performed transformations using Map Reduce, Hive to load data into HDFS.
5. Configured MR/Sqoop jobs to import data from RDBMS into HDFS.
6. Created HBase tables to store variable data formats coming from different portfolios.
7. Developed multiple Map Reduce jobs in Python/Java for data cleansing and preprocessing.

Experience

2-5 Years

Level

Junior

Education

M.S. In Applied Statistics

Description :

1. Deployed some flagship projects, such as Sales Forces allocation across points of sales based on business potential and image by using various sources of data (point of sales, sales data by SKU, Sales Rep data, social network, third-party data).
2. Prioritized outlets through social media data & automated updates to increase market penetration and better calibration of our route to market.
3. Gathered and organized large and complex data assets, perform relevant analyses and modeling.
4. Ensured analytics model quality assurance and validate them (peer validation).
5. Defined model monitoring criteria.
6. Communicated hypotheses and findings in a structured way.
7. Partnered with Data Analysts to present the outcomes of our models.

Experience

2-5 Years

Level

Junior

Education

Diploma