Manager - Recruitment at Scienaptic Systems
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Scienaptic - Senior Data Scientist (6-8 yrs)
Scienaptic is the world's leading AI powered Credit Underwriting platform company. Designed by seasoned Chief Risk Officers, its platform is creating industry leading business impact in terms of lifts such as higher approvals (15-40%) and lower credit losses (10-25%) with all the regulatory explainability. Last year alone, we have helped financial institutions evaluate 45 Million consumers and offer credit to over 15 Million. Scienaptics clients include Fortune 100 banks, community banks and Fintechs.
The Data Scientist role will enable you to be at the forefront of latest cutting-edge technology and create a significant and visible business impact for Scienaptic. You will be working with some of the best-in-class Coders, AI/ML Scientist and Business Analytics Consultants in an environment which will encourage you to contribute widely to functional and technological aspects without worrying about conventional job silos.
Responsibilities and Duties
- Design, build, test and deploy ML models at scale
- Experience with modern machine learning techniques including Ensemble Methods, Deep learning
- Write production ready code and deploy real time ML models ; expose ML outputs through APIs
- Analyse website and apps effectiveness and recommend changes to content, navigation and design
- Hypothesis Testing and Design of experiments to analyse and monitor results
- Experience in building digital enquiry generation models, product recommendations on website, marketing response models, social media analytics.
- Engineer features to improve decision algorithms
- Partner with data/ML engineers and vendor partners for input data pipes development and ML models automation
Skills and competencies
- Masters in Computer Science, Mathematical / ML related disciplines with 6+ years of experience into core ML
- Solid understanding of probability / statistics / data science / ML along with Python + SQL proficiency
- Test of hypotheses and analysis of ML models and optimizing models for accuracy
- Experience with Spark or other distributed computing systems for large scale training and prediction of ML models
- End to end system design: data analysis, feature engineering, technique selection, implementation, debugging, and maintenance in production
- Experience with unstructured data and text mining skillset is a plus