Job Location: Bengaluru
Credit Saison:
A Neo-Lending Conglomerate here to enable Indiaโs credit growth story, Credit Saison India, emboldened by our Global MNC parent, is here to accelerate Indiaโs credit growth story: by building a Technology-Led Neo-Lending Conglomerate. Across our verticals, we offer bespoke solutions to meet the various credit needs of Individuals, SMEs, FinTechโs, and NBFCs. Credit Saison India (โCS Indiaโ), having been founded in 2018, operates under the registered name Kisetsu Saison Finance India Private Limited as an MNC subsidiary of its parent company โ Credit SaisonCo. Ltd in Japan. Across our various business verticals like Wholesale Financing, Co-origination Financing, Consumer Financing, and SME Financing we look towards reaching resilient Assets Under Management (โAUMโ) of US1bn in record time.
More about us on https://www.creditsaison.in
A Neo-Lending Conglomerate here to enable Indiaโs credit growth story, Credit Saison India, emboldened by our Global MNC parent, is here to accelerate Indiaโs credit growth story: by building a Technology-Led Neo-Lending Conglomerate. Across our verticals, we offer bespoke solutions to meet the various credit needs of Individuals, SMEs, FinTechโs, and NBFCs. Credit Saison India (โCS Indiaโ), having been founded in 2018, operates under the registered name Kisetsu Saison Finance India Private Limited as an MNC subsidiary of its parent company โ Credit SaisonCo. Ltd in Japan. Across our various business verticals like Wholesale Financing, Co-origination Financing, Consumer Financing, and SME Financing we look towards reaching resilient Assets Under Management (โAUMโ) of US1bn in record time.
More about us on https://www.creditsaison.in
Roles & Responsibilities:
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Work with data scientists to refine the ML model and scale it up
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Create and maintain data processing, feature engineering and model training pipelines
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Design, develop, test, deploy, maintain and improve ML models/infrastructure and software that uses these models.
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Create re-usable tools and frameworks for ML model deployment and monitoring
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Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
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Be a go-to person to escalate production performance and evaluation issues for machine learning systems and their interactions with the rest of the ecosystem.
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Develop and maintain A/B testing frameworks
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Conduct internal workshops and external meetups
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Play a critical role in setting the direction in terms of project impact, ML system design and MLOps.
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Suggest, collect and synthesise requirements and create effective feature roadmap
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Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
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Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt.
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Manage individual project priorities, deadlines and deliverables.
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Participate in cutting edge research in artificial intelligence and machine learning applications.
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Contribute to engineering efforts from planning and organization to execution and delivery to solve complex, real world engineering problems.
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Code deliverables in tandem with the engineering team
Required skills & Qualifications:
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A Bachelorโs or Masterโs in computer science, with at least 5 -10 years of relevant work experience
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Experience in MLOps building production ML pipelines for model training/prediction
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Experience working with large data sets, coming from varied sources
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Experience working with open source ML libraries such as Tensorflow, PyTorch and XGBoost and strong understanding of Python.
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Experience working with ML model training/deployment tools (such as Airflow, Kubeflow)
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Familiarity with data engineering tools (Flink/Spark/Kafka etc)
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Experience with both object-oriented and functional programming concepts and language
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Experience in building and maintaining rule engines and A/B testing frameworks
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Experience in building, deploying, and improving Machine Learning models and algorithms in real-world products.
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Experience with application development and deployment in aws and sagemaker strongly preferred.
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