A Data Science Intern is a student or graduate who wants to take up a career as a data scientist. To learn the skills, and gain knowledge of the field the intern undertakes the following tasks mentioned on the Data Science Intern Resume – collecting data from all kinds of sources, from web SPIs to internal databases encoded in SQL; navigating datasets; using algorithms and programming for solving problems and to apply treatments, filters, and conditions for data; creating meaningful data visualization and communicating on findings to the Data Scientist.
To excel in this role, the intern should possess the following skills – engineering skills, knowledge of machine learning concepts; business communication skills; statistical and programming skills, familiarity with SQL and other programming languages, and expertise in statistical software. Most of these roles are undertaken by graduates from Engineering or Computer Science or Statistics stream.
Objective : Highly motivated professional with 4 years of experience in business analysis and product management. Gained proven expertise in building successful technology products in the financial technology space for investment banks. Aspiring entrepreneur and a product enthusiast.
Skills : Business Analytics, Product Management, Machine Learning, Data Science, Data Analysis, Big Data, Hadoop, Spark, Deep Learning, Predictive Modelling, Start-Ups, Statistics.
Description :
Streamlined and edited SAS and SQL code for client data retrieval and preparation.
Optimized runtime for various programs, reducing runtime by 25%+ in some modules.
Standardized code structure across multiple modules.
Updated and clarified program documentation Analyzed a large data set of customer responses to a client's newsletter.
Created SAS programs to retrieve customer response data from the client's big data repository.
Designed models to represent customer's pattern of response.
Analyzed the probability of different response patterns.
Experience
0-2 Years
Level
Entry Level
Education
BA in Computer Science and Economics
Data Science Intern Resume
Objective : An accomplished and dynamic Economist and Data Scientist with a broad skill set and wide range of experience, including financial markets, statistics, business, machine learning, politics, and programming. Significant experience in large database creation, management, and analysis. Adept at team and project management, with experiences in leading projects and teams in multi-cultural environments in underwriting, insurance, finance, politics, and hospitality.
Participated in a Data Science Internship focused on collecting, analyzing, managing, and interpreting data in the Group Underwriting Strategy department of global reinsurance company Swiss.
Analyzed various project requests from senior management and executives and developed strategic plans for accomplishing project tasks.
Acted as a project manager, outlining project structure and goals, assigned roles, and schedules.
Reviewed data records for accuracy and completeness.
Developed and managed internal social media usage.
Cleaned and managed database containing 48 million+ data points using econometric and machine learning to isolate core drivers of change and predict impacts.
Identified unique trends in claim frequency and severity that had a direct impact on business operations through a detailed analysis of the database and initiation of industry-wide trends research utilizing Excel, STATA, and R Studio.
Experience
2-5 Years
Level
Junior
Education
MS in (Magna Cum Laude), Applied Economic Analysis
Data Science Intern Resume
Objective : Looking for a full-time position in a competitive setup where one will be able to contribute to the firm's progress substantially and learn new skills. Eager to apply research work to industry data and continue innovating and developing new ideas.
Skills : Data Analysis, SAS, R.
Description :
Built predictive models for surety bond exposure risk.
Used SAS EG and R to model repeated measures data with a non-normal error term.
Used beta regression with an AR(1) covariance structure to build the model.
Weekly presentation of progress includes describing the statistical methodology used/ explored to non-statistician members of the team.
Researched and developed of a new approach for modeling percent of completion of work data.
Tried using basis splines to model the percent of completion of a surety bonded project.
Participated in corporate social responsibility engagements like Boston Food Bank volunteering.
Experience
0-2 Years
Level
Entry Level
Education
PhD. in Statistics and Probability
Data Science Intern Resume
Objective : Performed monthly quality checks of various MIS reports, ensuring the integrity of key metrics.Provided invaluable research, data analysis, and recommendations for pricing and portfolio risk model parameters in the course of coordinating and directing a team project; presented results to top executives.
Skills : Python, R, MATLAB, GAMS, C/C++, SQL, Java, And Mathematica, MapReduce, MPI, OpenMP, And CUDA.
Description :
Worked on a SaaS product that lets advertisers measure the effect their online campaigns have on retail sales.
Developed an interactive D3.js visualization and constraint solver to help clients explore the parameter space of their campaigns.
Wrote Python and R tools to query and analyze messy data from distributed Vertica databases, as well as 100GB+ MSSQL databases and Microsoft Analytics Services cubes.
Developed a tool to produce ad delivery zones around retail stores.
Assigned each household in the US to a retail store using drivetimes from OpenStreetMap routing.
Provided insight after the successful deployment using Shiny.
Designed and developed an analysis pipeline to detect transient events in time-series data from GPS signals.
Experience
2-5 Years
Level
Junior
Education
MS in Applied Mathematics
Data Science Intern Resume
Objective : Predictive modeler with a strong math background and experience in applying machine learning and statistics to solve a wide breadth of problems. Just submitted M.S. thesis in data mining and has 1+ years of experience in the field of developing predictive software to be embedded in a wearable device.
Skills : R, Python, SQL, SPSS Modeler, SPSS Statistics, Excel, Minitab, Data Mining, Data Analysis, Predictive Modeling, Machine Learning, EDA, Writing, Research, Leadership, Public Speaking.
Description :
Formulated a model development plan by comparing the pros/cons of various learning algorithms.
Prepared various datasets for modeling in R via cleaning, pre-processing, train/test set partition, custom subject-wise cross-validation schemas, feature engineering, EDA.
Trained, tuned, and evaluated numerous supervised learning algorithms to predict cardiac output based on pre-processed sensor data from the wearable device.
Implemented feature selection techniques where appropriate such as stepwise variable selection and recursive feature elimination.
Coded manual prediction functions for various models in R to be ported to C/C++ when embedded in an MCU.
Presented the analysis of each week in markdown reports, which were discussed in weekly conference calls.
Predicted diabetes patients' move patterns using Markov modeling and time series forecasting.
Experience
2-5 Years
Level
Junior
Education
MS. in Data Mining
Data Science Intern Resume
Objective : Data Science Intern will work on a wide variety of data science-related problems, with a focus on building predictive models for a variety of use cases.
Worked on the conversion of Teradata script for score calculation into hive query language and also into Impala query.
Implemented model scoring to rank each model based on their scores produced by Random Forest Classifier on PySpark.
Handled each partitioned data set on each node in batch to reduce the score calculation time for a model.
Worked on more than 100 Million data records.
Explored methods of tying user data together from multiple cookie IDs.
Investigated the origin of several power-law distributions in the ad/ID space.
Applied detailed forward modeling by simulating user behavior from online activity through the data collection process.
Experience
2-5 Years
Level
Junior
Education
B.Tech in Computers
Data Science Intern Resume
Objective : Exceeding Data Science Intern position expectations and took on higher-capacity responsibilities, including those of a Junior Analyst, Grouping move patterns for each day using hierarchical clustering, spectral clustering, categorical clustering, and autoencoder deep learning methods.
Skills : Excel, R, Arena, SAS, Access.
Description :
Worked on telecom customer's data.
Gave the data corresponding to different aspects of a node (like interface speed, in utilization, out utilization, CPU Max utilization, etc.).
Collected over a period of several months until the current day, the aim of the project was to predict the peak values of hourly max CPU utility for the following day.
Forecasted model and predictive models were built in R to calculate the hourly max CPU utility for the following day.
Worked with a 3 member team to help integrate the model into their tool.
Bestowed with the task of analyzing geographical coordinate data of our distribution fleet to develop software that can detect DOT violations such as going against traffic.
Developed the front end in HTML, CSS, d3.js, and leaflet.js to visualize offenses.
Experience
0-2 Years
Level
Entry Level
Education
Certificate in Database and Data Analytics
Data Science Intern Resume
Objective : Data Science Intern will work with the data science team to develop statistical methods and predictive models for user behavior. This role will also help implement these models into the product, and analyze the results.
Skills : MS Office, Data Science, Managing Skills.
Description :
Performed Distributions on Patients, Physicians, and Order Codes on LHCS (LabCorp Health Care System) database associated with Privia Clinic of size 16 GB (Rows: 50 million, Columns: 47 ) using Hadoop, Hive, Pig, Datameer, Tableau.
Built a predictive model on "Patient Readmission to LabCorp (Yes / No)" by performing Data Cleaning (16 GB to 100MB) using Hadoop, Hive, Pig, MySQL & wrote R Scripts for Data Pre-processing, Modelling using Machine Learning Algorithms.
Created Heat Maps, Bubble Maps using D3 software to reduce turnaround time by 10 minutes per Covance data request.
Built a recommendation system {Collaborative Filtering Technique} using Mahout, Java that recommends Tests to Patients.
Performed Twitter Sentiment Analysis using R on 1000 recent tweets with LabCorp in order to improve customer service.
Developed an in-house analytics platform for visualizing and analyzing customer use data.
Designed and implemented a custom algorithm for computing customer health scores.
Experience
0-2 Years
Level
Entry Level
Education
Ph.D. in Statistics
Data Science Intern Resume
Objective : Seeking Data Science Intern position which applies extensive experience in Statistical Methods, Data Analysis, and Machine Learning to critical questions in data-heavy services.
Skills : Research, Python, C, SQL, Unix, Microsoft Office, Mathematics, Data Mining, Data Analysis, Statistical Analysis, Statistics, Machine Learning.
Description :
Worked on AT&T AdWorks as a data scientist for the targeted advertising vertical.
Implemented customer segmentation using K-Means and did advanced classifications.
Created quantitative models for targeted accuracy for various customer segments.
Analyzed consumer behavior using structured and unstructured data to generate actionable insights.
Helped manage Hadoop and Oracle databases and ensured optimum operations.
Accomplished an R&D project of extracting personal information from negative news to structured records.
Reduced 88% manpower and 74% time compared with the current manual process.
Experience
2-5 Years
Level
Junior
Education
PhD in Physics
Data Science Intern Resume
Headline : Data Science professionals that have direct experience with online user behavior research, risk modeling, and statistical analysis, especially interested in e-commerce or credit risk management fields.
Designed the Nature Language Processing pipeline including sentence segmentation, regular expression tokenization, lemmatization, stemming, entity recognition, and relationship recognition.
Tools and Language Applied: Python, Natural Language Toolkit(NLTK), Scikit-Learn.
Optimized SQL queries in pgAdmin to retrieve data from the cloud (AWS) and created a local database.
Built predictive models from selected features (time, location, events, etc.), generated scores from several classification and regression models.
Did cross-validation from training & testing datasets and used clustering to visualize heat map for events in R & Tableau.
Designed and implemented a web-based interactive data visualization tool with the SARC Operations team to dynamically plot historical and predicted.
Analyzed the possibility of a low-latency overlay network in conjunction with satellite internet.
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