Master's degree or foreign equivalent in Data Science or related field.
Experience and/or education must include:
Designing data science approach, and developing custom algorithms to address business problems using Python, SQL, Spark, and Machine Learning.
Applying practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection using Python, SQL, Spark, and Machine Learning.
Extracting business insights from data and identifying the stories behind the patterns using data analysis skills and tools like PySpark, SQL and Tableau.
Distilling complex analysis and concepts into concise business-focused takeaways using data analytics skills and tools like Keynote and SQL.
Engineering novel features and signals, and pushing beyond current tools and approaches using software engineering skills and machine learning knowledge.
Deploying machine learning solutions to answer real-world questions.
Implementing data science-related applications in a programming language such as Python, Scala, or Java.
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses.
Using a querying language such as SQL to extract insights from data.