Manager - Analytics Consulting

Develop state-of-the-art analytics solutions for business problems

1. Manage various data analytics client projects, including the projects in pricing, marketing, supply chain management, etc.
2. Discuss key business objectives with the stakeholders, understand how business users and customer data is collected, and suggest appropriate data collection methods
3. Work with business executives to understand business constraints that may impact data science or machine learning models
4. Examine sample data and prepare a preliminary solution proposal document to present to clients
5. Plan data collection methods (E.g. Market Research, Internal Data, 3rd Party Data Vendors) & determine sample sizes. Suggest new data sources and advise team on how to simulate market scenarios to enhance data assets.
6. Consult the client on adoption of big data frameworks and educate business stakeholder on traditional data systems vs big data systems by preparing a cost-benefit analysis
7. Use the knowledge of data modeling, operations research, statistics to solve real world business problems such as fraud detection, cross-selling, dynamic pricing, etc.
8. An example problem in the area of Marketing, would be to identify the optimal targeting mechanism for business prospects such that we know which prospects could be targeted through email, which ones through social media and which ones through Display or Paid Search, to customize the message and offer , thereby saving costs and increase conversion for the client

Work on building and implementing Data Science and AI solutions

1. Use mathematical or statistical modeling techniques to perform exploratory analysis - build hypotheses, run regressions, find patterns, and document the solution approach
2. Extract, transform and organize the data into datasets using tools like SQL. Write complex SQL queries to retrieve data with low latency.
3. Validate results of the model by benchmarking against historical data collected by the business users
4. Report the results and insights using business intelligence tools like Tableau, QlikView
5. Present the results of predictive models by converting it to usable business insights

Supervise team of data analytics consultant and project management

1. Break down project goals into specific tasks involving business analysis, data analysis and data engineering. Divide and assign tasks for Business Problem Definition, Data Preparation, Exploratory Analysis, Model Development and Implementation, Model Validation and Testing, Insights Generation, Hypothesis Testing and Scenario Analysis, Presentation etc.
2. Ensure that the developed solution can be implemented in production by the client’s IT and engineering teams and meets the hardware and software systems requirements
3. Lead data collection, validation, and analysis activities including risk, spend, commodity and supplier information.
4. Benchmark the developed solution for cost savings or revenue impact as per the project proposal document and present the result to business leaders

Contribute to Org building activities

1. 1Build internal analytics modeling IP and accelerators for Tiger by providing insights into what business users are looking for and what they would pay for it
2. Support business development team in winning new data analytics projects by providing proof-of-concept solutions
3. Recruiting interviews to hire new employees to build world-class analytics talent
4. Work with clients and Tiger solutions team to come up with analytics platform and solutions such as automated insurance underwriting, market mix modeling, augmented text processing
5. Write business analytics project proposals and make case study presentations to showcase company capabilities

Job Requirements:
Education Qualification: Bachelor's Degree

*Salaries may increase annually based on performance. Additional bonuses may be issued at the company's discretion and comparative market trends. If issued, the bonus may be in the form of Cash or ESOPS. COLA may be added as well at the company's discretion.