This interesting role works with functional departments to define business problems and devise data-driven solutions. The process involves employing sophisticated analytics programs and statistical methods to prepare data for use in predictive and prescriptive modelling and designing and developing analytical models. Through analysis of data, you will identify opportunities for sustainable value creation and build innovative capabilities for the organization.
You will communicate predictions and findings on key industry topics and analytics projects to management through effective data visualizations and reports, with the objective of supporting fact-based decision capability. You will also support the dissemination of analytics knowledge and sharing of experience within the team and the business users, and drive adoption of structured analytic methodology (AMP) for identification and implementation of analytics projects.
The successful candidate should possess the following:
- Degree in Computer Science, Economics, Mathematics or Statistics
- Postgraduate degree majoring in data analytics or machine learning preferred
- Minimum 2 years of relevant work experience
- Preferable experience with statistical and analytical modelling, knowledge of analytic tools and big data technologies.
- Should be able to work with tools to clean, transform, manipulate, model and visualize large amounts of data.
- Minimum skillsets required:
- Deep experience with languages like R, Python, SQL, Excel
- Experience in Data Cleaning, Sampling, Balancing, Imputation using R, Python
- Experience in Statistical modelling techniques like Anova, Hypothesis Testing (t-test, chi-sq), Linear regression,
Logistic regression, Decision trees, Neural Networks, Random Forests, Bootstraping, Clustering, Classification,
Factor Analysis, K-cross validation
- Knowledge of Big Data frameworks/ technologies: HIVE, Spark or similar frameworks
- Data visualization tools: Qlik or Tableau
- Ability to communicate complex ideas to technical and non-technical audiences
- Ability to analyze numbers, trends and data to derive conclusions.
- Effective oral and written communication