Job description:
Assist algorithm researchers in developing and optimizing recommendation systems to enhance user experience and platform revenue. Utilize machine learning and data mining techniques to analyze user behavior and build personalized recommendation models
Research and develop recommendation algorithm workflows, including but not limited to recall, user profiling, etc.
Analyze user behave or data to mine user preferences and enhance the accuracy and diversity of the recommendation system.
Conduct A/B tests to evaluate algorithm effectiveness and continuously iterate and optimize the model.
Collaborate with product managers and engineers to integrate recommendation algorithms into products.
Stay up-to-date with the latest advancements in recommendation system research and apply cutting-edge technologies to actual products.
Basic Qualifications:
BS/MS in Computer Science/Engineering or a related technical discipline.
Familiar with at least one programming language such as Python, Java, or Scala.
Proficient in SQL and scripting languages such as Bash.
Have experience in handling large data sets using big data technologies such as Hadoop and Spark.
Have basic understanding of the principles of machine learning, algorithms and evaluation metrics of recommendation systems, with prior experience in building algorithm models for the internet preferred.
Have good data analysis skills and problem-solving abilities.
Good teamwork spirit and communication skills.
Clarified Qualifications:：
Prefer 5+ years working experience
Prefer candidates with experience in well-known internet e-commerce business or have recommendation algorithm-related projects.
Smart, quick learning and proactive
Dikshatek
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