Hewlett Packard (HP Bangalore) invites internship applications for Data Science/ AIML intern for the year 2021. Online applications open on the official website.
The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must be comfortable working with a wide range of stakeholders and functional teams.
- Education: 10th + 12th + B.E/B.Tech
- Streams-Electronics & Communication, EEE, Computer Science, Information Technology ( 2021 batch)
- Percentage: 10th + 12th + B.E/B.Tech marks/aggregate to be 60% and above with no arrears.
- Strong problem solving skills with an emphasis on product development.
- Knowledge of using statistical computer languages (Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
- Knowledge of working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- Knowledge in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Develop testing framework and test model quality.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
- Distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.