Job description
LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.
Searching for your dream job? At LinkedIn, we strive to help our employees find passion and purpose. Join us in changing the way the world works.
If you are an applied research engineer/scientist with a passion for working on massive semi-structured text and graph datasets, then the LinkedIn Data Team is the place for you. The ideal candidate will have domain experience (data mining, information retrieval, security data science, natural language processing, advanced statistics, and/or machine learning), a strong systems orientation, and experience in building data mining products. The work you put forth will directly impact and fuel LinkedIn’s search relevance, ad targeting, information extraction, and recommendations.
• Work with BIG data, crunching millions of samples for modeling data mining, recommendation, or search relevance solutions.
Basic Qualifications:
• BA/BS Degree in Computer Science, Machine Learning or related technical discipline, or 6+ years of related practical experience.
• 2+ years experience in software design, development, and algorithm related solutions.
• 2+ years experience programming experience in Java, C/C++
Preferred Qualifications:
• BS + 5 years of relevant work experience, MS + 4 years of relevant work experience, or PhD +2 years of relevant work experience
• Working knowledge in one or more of the following: machine learning, data mining, information retrieval, security data science, advanced statistics or natural language processing.
• Experience with iterative, test-driven development.
• Experience with configuration management (SVN, GIT, ant, maven, etc.).
• Experience with developing and designing consumer-facing products.
• Experience with Hadoop, Pig, or other MapReduce paradigms.
• Knowledge of internals Lucene/SOLR or other information retrieval systems.
• Published work in academic conferences or industry circles.