Junior Data Scientist Job in Mumbai at Aramex Logistics

Aramex is hiring for the role of Junior Data Scientist!

Responsibilities of the Candidate:

• Working under the guidance of senior Data Scientists to execute strategic keystone projects.
• Gaining a thorough understanding and know-how of the on-premise and cloud-based data warehouse and data lake.
• Continuously keeping updated with the latest AI and ML technologies.
• Extracting relevant data from data warehouses such as AWS Redshift to be used for Data Science projects.
• Data cleaning and data imputation of unclean data.
• Performing a thorough exploratory data analysis and presenting results to relevant stakeholders for insight generation.
• Featuring engineering relevant to the purpose of the Data Science problem.
• Creating and evaluating data models using statistical, algorithmic, data mining, deep learning, visualization, and data matching techniques for data discovery and intelligent automation.
• Presenting and summarizing modeling results and recommendations to business users and stakeholders in an understandable and relevant way, verbally and visually.
• Documenting and publishing analyses, instructions, and code so others can replicate and learn from previous work.
• Educating the organization about approaches and analytical principles to support the organization in the application of novel data science and advanced analytical techniques.
• Leading or participating in the development, testing, and deployment of production-ready code.
• Preparing and presenting progress reports and results to stakeholders.

Requirements:

• Pursuing Bachelor’s in computer science, Operational Research, Statistics, Applied Mathematics, Engineering, or Natural Sciences or 1+ years of experience as a Data Scientist.
• Ability to write clean, documented production-ready Python code.
• Most importantly an Inquisitive mind and the ability to independently ask questions, find answers, learn, and move things forward.
• Understanding of data analysis using the Pandas library.
• Strong knowledge of, and the ability to explain statistical and mathematical concepts and techniques for quantitative analysis.
• Supervised Machine Learning Algorithms like Logistic Regression, Bayesian Approach, Decision Trees, Support Vector Machines, Ensemble Methods, Feature selection techniques etc.