You care about more than just you, Current student, pursuing an MS or PhD in Computer Science, or Electrical Engineering and will be graduating between December 2017 and June 2018, Actively engage in rapid prototyping of new technologies within the Big Data technology landscape, Challenge current best thinking, test theories, evaluate feature concepts and iterate rapidly, Proficient in Microsoft Office applications, Deep engagement with documentation of semi-conductor data and process, Strong team-player who can collaborate with colleagues, Working through the full flow of very challenging data problems anywhere from data cleaning, to building a concept of the model to extracting the right features and testing the model to drive better decision making through various data and statistical modeling techniques, algorithm development involving real-world noisy data, Assist the Director of the team in preparing information related to solving for internal process improvements, Dive in and work with our data science team to develop new data-centric products involving new and innovative algorithms, Perform analysis and develop analytical models to maximize SEM revenue growth, Process Optimization â Propose potential research-on-research tests to improve current Nielsen methodologies and improve response and compliance, Identifying opportunities for improvement within existing software applications and frameworks, Using current programming languages and technologies, writes code, completes programming, and performs testing and debugging of applications, Participating in development of analytical models using Machine Learning, Ability to produce quality work products with attention to detail, Excellent communicator. First of all, let’s quickly go over what sections I have on my résumé. These include solid knowledge of supervised vs. unsupervised learning algorithms, including linear and logistic regression, polynomial regression, regression splines, general additive models, decision trees (bagging, random forests, boosting), support vector classifiers, k-nearest neighbor, k-means clustering and principal components analysis, Exposure to at least one advanced machine learning application, such as autonomous robotics, computer vision, or medical diagnostics, Comfortable selecting and applying resampling methods (LOOC, k-fold CV, and bootstrap), Understanding of how to regularize models (subset, shrinkage, and dimension reduction), Extensive experience with data preparation and normalization for modelling, Deep knowledge of R and the open source ecosystem around it. This section, however, is not just a list of your previous data scientist intern responsibilities. This is why you need to provide your: The section work experience is an essential part of your data scientist intern resume. Include your key skills across your data scientist resume and not just in the key skills section. Cover letter tips will help to get things … • Innovative new ads products Tips and examples of how to put skills and achievements on a data science resume. • Direct involvement with P30 grant submission • Five years of related experienc... • Strong creative thinking and problem solvi... • Strong leadership and communication skills... • Innovative problem solving skills, solid u... • Perform or assist in routine veterinary procedures and surgery preparation Look through cover letter examples on the … Apply to Data Science Intern, Analytics Intern, Data Scientist and more! preferred but not required, Analyzes historical trends using statistics and programing languages (R, SQL, Python, Java) to provide recommendations on how to increase revenue or reduce costs, Experience or practice writing programs in PL/SQL, R, STATA or similar statistical package, Experience or practice writing data scrubbing routines in a procedural language, Collaborate with business on requirements to refine the projects goals, scope and timelines, Collaborates with technology for coding standards, data access, data security, data interpretation to build predictive analytics models, Develops models that can be deployed, operationalized and used by the business, Work with senior data scientists using data mining techniques, machine learning algorithms to solve online advertising fundamental problems, Design proofs of concept and evaluate performance of such models, As part of a team, develop, test, and integrate critical machine learning models into production, Be responsible for retrieving data from hadoop data warehouse, cleaning up, analyzing, modeling and presenting results to product managers and engineers, Collaborate with product, engineering and operations teams, Eager to learn new technologies, have curiosities and want to work on large-scale dataset (billions of records per day), Are enthusiastic about realizing your ideas into real product, Want to work as part of collaborative team and develop communication skills, Database, data structure knowledge, such as big data, hadoop, etc, Ability to work up to 40 hours per week for the summer, Answers phones and takes messages or provides information, Assists with projects to ensure deadlines are met, Regular, consistent and punctual attendance. Python, Perl, Minimum of 3 months experience with programming languages like Java, C/C++, SQL, Minimum of 3 months experience with internal business segment stakeholders, Minimum of 3 months experience with Machine Learning, Operation Research, and Statistics, Develop software, algorithms, and applications to apply mathematics to data, perform large-scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy, Assists business with casual inferences & observations with finding patterns, relationships in data, Eager to take on challenges and complete tasks within given timelines, Ability to multitask, self-motivated and be able to work independently, Ability to work in a dynamic and team-oriented environment, Meet with decision makers, system owners, and end-users to define business requirements, Conduct research on software products and solutions, Participate in design sessions, prototyping solutions on distributed platforms, Review, understand, and analyze the effectiveness and efficiency of existing predictive modeling platforms and recommend new strategies for improving, or further leveraging, those systems in the future, Contribute to planning, design, development, and deployment of predictive model based applications, Prepare and deliver reports, recommendations, or alternatives that address or improve the existing and potential predictive modeling process, Coordinate and perform tests including end-user reviews, Collaborate with fellow interns on challenging Group Projects throughout summer, Engage with the local community through various outreach and community service events, Must be pursuing a degree in Engineering, Computer Science, Software Engineering, Mathematics, Statistics, Information Technology or related discipline, Must be able to participate in the internship prior to completing your current degree program, Must be a U.S. Citizen or Permanent Resident due to export control restrictions, Passion for using, developing, analyzing, and learning about new technologies related to predictive modeling, distributed computing and data engineering, Foundational business acumen and desire to improve your business knowledge, Prefer background in modeling language(s) (R, Python) and distributed computing (Hadoop ecosystem), Students pursuing an advanced degree preferred, Develop data-driven insights that will lead us to a deeper understanding of how the human body works, Develop machine learning solutions capable of working across a wide range of technologies, Continuously interact with product owners and product managers in order to convert technical solutions into advanced features, Has a deep interest in working with large data sets (~100 billion records per day), (a plus) has some familiarity with data mining tools like Apache Spark or Hadoop MR, Handle ad hoc data analytics request from the Digital Innovation team, Acquire knowledge of Grainger's various data stores and 3rd party data marts at a rapid speed, Provide guidance to the Digital Innovation team on the appropriate tools and methodologies for discovering insights through data, Create and program predictive models to enable predictive applications, Investigate and solve exciting and difficult challenges in image recognition, classification, and deep learning, Train scalable computer vision and machine learning solutions to hard problems, Help design and implement full-stack computer vision solutions for millions of Covet Fashion customers, Use the latest advances in neural networks and machine learning to bring new experiences for our customers, Major in Mathematics, Computer Science, Bioimaging or other engineering disciplines, Current enrollment in a graduate-level program preferred, PhD or MS Students (preferably in their last year) in computer science, applied mathematics, or other quantitative computational discipline, Experience with open source machine learning and statistical analysis tools, Coding experience, either in Python or R (knowledge of both is a plus), Ability to communicate complex ideas in data science, Good knowledge at least in a few of: multivariate regression, random forests, classification algorithms & learning methods (supervised and unsupervised), Gaining basic understanding of gathering business requirements through staff interviews and other data collection methods, perform analysis, document process flows, track projects, and develop reports, Clearly and concisely communicating with equity analysts and associates, Understanding of the investment management business, securities industry and business operations, Strong analytical and quantitative skills, Must be pursuing a graduate degree in Computer Science, Data Science, or Statistics, Must have advanced knowledge of R, Python, database technologies, ETL techniques, and MS Excel, Must be comfortable pre-processing (cleaning, normalizing, etc.) A Master 's in 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