Data scientist is responsible for fetching information from various sources and using statistical and analytical methods plus AI tools to automate specific processes within the organization and develop smart solutions to business challenges.
● Data mining or extracting usable data from valuable data sources.
● Carry out preprocessing of structured and unstructured data.
● Process, cleanse, and validate the integrity of data to be used for analysis.
● Use machine learning tools to select features, and create and optimize classifiers.
● Develop prediction systems and machine learning algorithms.
● Present results in a clear manner.
● Collaborate with Business and IT teams.
● Master's degree in Computer Science, Statistics, or similar fields.
● Programming skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL.
● Statistics – good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
● Machine learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, and Decision Forests.
● Data wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist's job description.
● Excellent communication skills – ability to describe findings to a technical and non-technical audience.
● Ability to independently research, implement, test, and deploy data science and machine learning technologies.
● Problem-solving aptitude.
● Excellent communication and collaboration skills – experience in writing and presenting comprehensive narratives on opportunities, objectives, goals, and delivery plans to customers and stakeholders.
● Self-sufficiency in big data technologies, such as Map Reduce, Spark, and Hive, and familiar with NoSQL databases.