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Location

Bangalore | India

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Job description

At SAVii, we believe a salary is more than just take home pay. In fact, we believe one's wages is the key to financial wellness, a vehicle to stability and empowerment. Through salary deduction, we can help employees maximize other financial solutions that were designed to help them. At SAVii we think fast, and excellence is an attitude. We give our team the license to dare so that everyone can learn and succeed. Our shared culture of respect is built on these core values: Transform Lives Everyday | Embody Integrity | Stronger Together.

The Data Team acts as a central hub for asking analysis questions. We are a small team of developers and consultants who believe in impact driven work. We believe in democratisation of data and are major supporters of knowledge distribution to empower the company. We don't shy away from getting our hands dirty whenever it comes to anything data and we demand critical and collaborative debate when tackling problems.

As a Data Scientist, you will collaborate building and implementing predictive models and automate decision-making. Overall, this role is responsible for designing machine learning systems, which involves assessing and organizing data, executing tests and experiments, and generally monitoring and optimizing machine learning processes to help develop strong performing machine learning systems. You will work on varied subjects across the organization across different data models and stakeholders. Specific responsibilities will include:

Duties and Responsibilities

• Designing, developing, and researching Machine Learning systems, models, and schemes
• Training and retraining ML systems and models as needed. Verifying data quality and/or ensuring it via data cleaning for training data
• Deploying models in the production environment
• Performing statistical analysis and using results to improve models
• Identifying differences in data distribution that could affect model performance in real-world situations
• Monitoring model performance vs basic statistical methods for cost-benefit analysis as well as deployment performance and adherence to specifications
• Produce and maintain all documentation related to data models or analysis
• In addition, the Data Scientist may be tasked to lead other special projects from the VP of Data or Chief Risk Officer

Qualifications

• Background in Credit Risk. If none, candidates with backgrounds in epidemiology or actuarial science may apply
• Minimum 3 years experience as a Data Scientist or related field (ML Modeller, Actuarial, Epidemiologist). If currently engaged in academic research, postdoctoral experience will also be considered
• Deep analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Extensive experience in Python and its related ML libraries in deploying machine learning models (decision trees, survival analysis, time series analysis, neural network)
• Has previously developed solutions end to end (data pipeline from data collection to model training & deployment)
  

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