• Performing data wrangling and exploratory data
• Must have extensive Propensity Modeling exp.
• 5 years of experience in data science and big data

Job Purpose

To communicate and provide stakeholders with business-focused findings or actionable insights for their decision making, this position organize and analyze large amounts of unstructured and structured data by utilizing various data science tools together with programming languages.

Key Responsibilities

• Work collaboratively with data engineers and data architects to acquire new data from internal and external source systems.
• Support business initiatives and projects by performing data wrangling and exploratory data analysis, discovering trends and patterns, building predictive models and machine learning algorithms, etc., based on the CRISP-DM methodology and agile approach.
• Stay up to date with big data and analytical techniques, such as machine learning, deep learning and text analytics.
• Provide analytics expertise, directions and guidance to business leads through turning insights into business action so as to improve sales and customer profitability.
• Present summary of analyses including data monetization on large datasets using advanced analytics tools and data visualization techniques.
• Lead implementation of AI models and business rules incorporated in automated business processes.

Qualifications

• Bachelor's degree or higher in Data Science, Statistics or related fields.
• Must have extensive hands-on Propensity Modeling experience
• Statistics modeling skill, e.g. linear regression, logistic regression, decision tree, neural network, random forest, k-means, SVM and XGBoost.
• Programming skill, e.g. SAS, R and Python, with strong business acumen.
• Be able to clearly interpret analytics results and lead to the business execution.
• Certification / License: AI and machine learning professional
• More than 5 years of experience in data science and big data using tools, e.g. SPSS, SAS, Alteryx, Spark, Jupyter Notebook and Databricks.