Analytics Manager

Designation:

Location:

Broad Objectives:

Work with large volumes of data collated from multiple data sources to create relevant databases that are leveraged to help solve business problems.

Leverage predictive statistical models, machine learning and newer technologies like deep learning, artificial intelligence to derive business insights and facilitate effective decision making.

Roles & Responsibilities:

Data Preparation

• Understand the data architecture to identify the data source table and ensure all required fields can be fetched.
• Create dataset for the model by collating and creating databases from multiple data sources.
• Work with the data warehouse team to fetch data points from the system and ensure all required fields are covered.
• Clean, analyze and feature engineer the data to derive a useable dataset.
• Perform profiling and exploratory data analysis to transform the data for model building.
• Apply business knowledge to derive new features from the existing dataset for model building.
• Document the various stages of data cleansing and preparation for future reference.

Model Building & Validation

• Use predictive, prescriptive and descriptive models to provide insights to solve business problems.
• Develop machine learning techniques to improve model accuracy.
• Tune the model parameters to reduce overfitting and improve overall accuracy.
• Develop, maintain and run test tools to investigate different aspects of the model.
• Set up and run back-testing on historical data to derive model accuracy.
• Perform independent model validation on multiple test datasets to improve robustness of model.
• Document the multiple iterations of model building and validation for future reference.
• Assess and consider all kinds of risk to review and make informed decisions around new initiatives or responses to situations.

Data Visualization

• Design and develop strategic and analytical dashboards on tableau to visualize the insights.
• Derive metrics and features to visualize the data to make it more comprehensible.
• Use visualization to uncover hidden patterns in the data
• Develop dashboards to monitor and analyze the trend in business.

Capability Enhancement

• Engage in regular learning and training to stay up to date with the latest trends in data science field.
• Design and develop deep learning or artificial intelligence techniques to drive innovation.
• Develop and design new to industry/ first of a kind analytics products or initiatives to increase efficiency.