Data Scientist

Responsibilities :

Industry knowledge- Knows basic principles of industry lexicon, competitor landscape, sub-verticals and related best practices in order to provide suggestions for specific functional processes. Basic understanding of industry standards to document current customer compliance and gaps. Functional/Process knowledge- Shows the basic understanding of processes in relevant functional areas (such as Telecom - Fulfillment, Assurance, Workforce Management, Billing etc.) in order to Document or guide documentation of simple as-is customer processes Appreciate the context of customer requirements from specific engagements Ability to suggest Analytics algorithms to use based on business situation mindful of fundamental assumptions in the algorithms OR Work with other data scientists as a team to understand algorithms suggested and provide QA in algorithm choice from a business perspective Align our deliverables to customer requirements, provide business acumen to avoid apparently bookish or theoretical output Ability to converse with customers on rationale for an approach taken, pros and cons, etc. Responsible for successful delivery of Advanced Analytics solutions and services in client consulting environments experience in optimization (linear, mixed integer, constraint programming), simulation, and/or predictive analytics using AAO tools, such as SAS or SPSS and other Tools R and Python. Define key business problems to be solved formulate mathematical approaches and gather data to solve those problems, develop, analyze/draw conclusions and present to client. Assist clients in identifying type of analytics and management data that will directly relate to improving clients' market share or any other measure client is addressing. Identify the differentiators, map them to present-day environment, and then design an improvement plan. Discover new opportunities to optimize the business through analytics and statistical modeling. Oversee all aspects of analytics and business intelligence projects if necessary.

Additional Responsibilities:

Analytical ability- Looks at data from multiple sources and integrates data/inputs in a manner to build cause effect linkages to arrive at key issues. Uses understanding of the problem to arrive at multiple solution alternatives keeping in mind the various stakeholders and assess the pros and cons of all the alternatives to arrive at the optimal solution Business acumen- Understands the linkages of metrics and end objectives to key business drivers and aligns team efforts to deliver on it. Demonstrates basic understanding of business financial parameters and is aware of business value impact of activities and decisions taken by him/her and team. High Impact Communication- Assesses the target audience need, prepares and practices a logical flow, answers audience questions appropriately and sticks to timeline.

Technical and Professional Requirements:

Preferred Proficiency with statistical analysis tools (e.g., SAS, SPSS, R & Python) Hands on experience in Statistical Techniques & Deep Learning such as Decision Tree, Segmentation, Logistic and Multiple Regression, and others Experience of Forecasting, Campaign Management and Customer Segmentation is desirable Strong Excel, Access and PowerPoint skills Familiarity with database query tools (SQL) Basic understanding of data warehouse architecture Understanding of various Analytical Tools, Platform & Frameworks.

Full time