Data Scientist

Position : Data Scientist

Company : IT Company of 35yrs

Location : Mumbai suburbs

CTC : 24-25LPA

Education : B.Sc/M.Sc/BCA/MCA – IT or Computer Science

Exp : 10yrs +

Notice : immediate only

Domain Exp : Insurance and / or Finance (preferred)

Interview Style : R1> Assessment/R2>R3

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

Accountable for designing and implementing data-driven solutions that contribute to business value by leveraging statistical models, machine learning algorithms, data mining, and advanced visualization techniques.

Non - Nego Skills :

• 8+ years data analysis experience within an insurance environment
• Extensive experience with at least one programming language (e.g. Python), business analytics software (e.g. SAS) statistical package (e.g. R)
• Experience in database language (e.g. SQL)
• Deep theoretical understanding of statistical methods and machine learning techniques
• Understanding of Artificial Intelligence solutions and techniques
• Ability to apply statistical methods and machine learning techniques to solve business problems
• Formulating business problems to enable statistical modelling
• Selecting the right statistical tools and techniques for the job
• Experience translating statistical findings into business recommendations

Role to play :

• Identify and develop Predictive and Prescriptive Models to enable better decision making of business.
• Identify, understand and interpret data structures across various databases within the business to facilitate data analysis and continuous monitoring activities.
• Delve into insights in data and processes to help improve the business.
• Compare model performance, select the best algorithm for the job and be able to motivate this choice in a non-technical manner.
• Interpret results and translate findings into clear and actionable insights that can be easily validated with the project sponsor.
• Communicate findings to business with various skill levels and in various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights.
• Assist business users in the use of the models and interpretation of model output.
• Contribute to the process of negotiating objective and realistic service level agreements, monitor appropriateness and recommend adjustments.
• Define service practices which build rewarding relationships, encourage innovation and allow others to provide exceptional client service.
• Deliver on service level agreements made with clients and internal and external stakeholders to ensure that client expectations are met.
• Make recommendations to improve client service and fair treatment of clients within area of responsibility.
• Participating in and contributing to a culture which builds rewarding relationships, facilitates feedback and provides exceptional client service.
• Enable the realization of the financial business benefits accruing including minimization of operational costs by ensuring that solutions are implemented effectively.
• Model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions.
• Participate and/or lead discovery processes with business stakeholders to identify problems and opportunities that may be addressed with statistical modelling or machine learning.
• Collaborate with business to define approach to resolution of key business problems or development of new business strategies.
• Contribute to the business by highlighting possible opportunities for process improvement and business value creation.
• Identify and develop the hypothesis testing framework and modelling approach to address the business requirements.
• Identify available and relevant data, potentially leveraging new data collection processes such as social media.
• Make strategic recommendations on data collection and experimental design incorporating business requirements and knowledge of best practices.
• Prepare the data for analysis and modelling, which includes data cleaning, standardization, transformation, dimension reduction and feature engineering.
• Identify and train suitable models/algorithms to discover patterns and make predictions.
• Extend existing code and develop custom code to implement statistical models, machine learning algorithms and data mining techniques for large datasets in a computationally efficient manner.

Interested candidates write to [Confidential Information] & call at / whats app at - 7700 982609