Analytical and Problem solving, Data Analysis, Data cleaning / Data cleansing, Data science techniques, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Python Programming, R Programming, Transformer, XGBoost
Siemens Industry Software Inc.Strategic Student Program (SSP) Discover your career with us at Siemens Industry Software! We are a leading global software company dedicated to the world of computer aided design, 3D modeling and simulation— helping innovative global manufacturers design better products, faster! With the resources of a large company, and the energy of a software start-up, we have fun together while creating a world class software portfolio. Our culture encourages creativity, welcomes fresh thinking and focuses on growth, so our people, our business, and our customers can achieve their full potential. We’re currently recruiting students for our Summer 2024 Strategic Student Program. Our intern positions will allow you to find a career path that most inspires you. Here, you will apply your education to solve real-world problems, and turn theory into practice. At Siemens, our goal is to empower our students to become the next leaders of our company.
Baseline Requirements:
Data Engineering/Science Internship
Ready to dive into the exciting world of data science and machine learning? Join us at Siemens as a Data Science Intern for a dynamic summer internship filled with exploration and innovation. As a crucial member of our team, you'll take the lead in unraveling the mysteries hidden in a large subset of our vast customer feedback data through an immersive Exploratory Data Analysis (EDA) process. Once this exploration is complete, you will prepare the data set for future machine learning.
Key Responsibilities:
Data Cleaning : Implement thorough data cleaning processes to guarantee the integrity and quality of the datasets.
Exploratory Data Analysis (EDA): Conduct a comprehensive EDA process, extracting valuable insights from our customer feedback data. Your contributions will deepen our understanding of user behavior and preferences across key product lines.
Data Set Curation: Lead the meticulous creation of datasets crucial for future machine learning applications, ensuring data cleanliness and organization.
Idea Categorization: Dive into categorizing ideas based on problem areas or ideation themes, collaborating closely with machine learning and product teams for streamlined dataset structures. Your contributions will play a vital role in shaping inputs for our machine learning algorithms, fostering a nuanced understanding of patterns for innovative solutions. This role offers hands-on experience in the dynamic realm of machine learning data preparation.
Qualifications:
This internship offers you:
Join us for an enriching internship experience where you can apply your skills, contribute to meaningful projects, and gain valuable insights into the dynamic field of data science. Ready to make an impact? Apply now!
Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.
Siemens is a technology company focused on industry, infrastructure, mobility, and healthcare. Creating technologies for more resource-efficient factories and resilient supply chains to smarter buildings and grids, to cleaner, comfortable transportation and advanced healthcare, the company empowers customers to transform the industries that form the backbone of economies, transforming the everyday for billions of people.
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