We’re always looking for talented peoples who think out of the box.
KEY RESPONSIBILITIES
Using machine learning tools to select features, create and optimize classifiers
Carrying out preprocessing of structured and unstructured data
Enhancing data collection procedures to include all relevant information for developing analytic systems
Processing, cleansing, and validating the integrity of data to be used for analysis
Analyzing large amounts of information to find patterns and solutions
Developing prediction systems and machine learning algorithms
Presenting results in a clear manner
Propose solutions and strategies to tackle business challenges
Collaborate with Business and IT teams
Skills
Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
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, Decision Forests.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.
