Senior Data Scientist
Senior Data Scientist
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Job Description
About Company:
Spocto () a Yubi Company () is a big data ytics company on a mission to revolutionise the digital debt collections industry. Spocto is a fintech company that uses Artificial Intelligence (AI) & Machine Learning (ML) to enhance customer reach engagement and interaction; Spocto is a pioneer in disrupting the debt collections industry with intelligence.
With proprietary algorithms we strive to bring dignity into the debt collections process ensuring better customer experience and resulting in improved customer relation and retention. ociated with 30 BanksNBFCs & processed over 450Mn Transactions. Our Contactless engagement with the B2B clients has strengthened our relationship with the Top performing banks & NBFCs in India and UAE.
As we continue to grow and disrupt the market through our innovative solutions we are now part of Yubi Indias first and largest institutional debt platform that provides fullstack debt infrastructure across discovery and fulfillment. In March 2022 Yubi became India s fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. Yubi is backed by marquee investors like Insight Partners B Capital Group Dragoneer Sequoia Capital Light Speed and Light Rock and are the onlyofitskind debt platform globally revolutionising the segment.
Responsibilities
Ability to yze the data and understand the problem from a data perspective.
Ability to build structured (clic machine learning models) and unstructured models (NLP text mining)
Ability to understand the predictions and accuracy. Communicate the same to internal stakeholders with next steps on what can improve the accuracy.
Work with internal business stakeholders to continuously improve the models.
Work with the MLOPs team to deploy the model.
Work with the Data Engineering team to ensure the data pipelines for model training are built in an optimized way.
Work with the Product Management team to integrate the deployed model with business product
Willingness to work and learn in a very fast paced environment.
Ss Required
Previous experience in building a campaign recommendation engine. This role is for the
24 yrs of experience in Python SQL (Structured relational DBs) Statistics Machine Learning models basic NLP and text mining.
Good to haves AWS services like sagemaker s3 athena; mlflow; understanding of unstructured DBs like mongo; GenAI
Key Responsibilities Align data solutions with business objectives and technical constraints, adapting to the evolving market dynamics, regulatory landscape and client requirements. Work closely with cross-functional teams, including data engineering, product management, and business teams, to manage and lead various aspects of the product lifecycle, from conception to delivery. Monitor model performance and maintain risk management protocols by retraining models as needed, ensuring ongoing accuracy and regulatory compliance. Stay updated on industry trends, regulations, and emerging technologies to continuously improve the models and the platform. Provide mentorship and guidance to junior data scientists and engineers within the team. Required Ss Technical Ss In-depth understanding of machine learning algorithms (supervised, unsupervised, ensemble ods) and their application to credit risk. Expertise in statistical ysis, including hypothesis testing, regression ysis, probability theory, and data modelling techniques, to extract insights and validate machine learning models. Experience in designing, developing, and delivering end-to-end data products and solutions. Expertise in model explainability techniques (e.g. SHAP, LIME) and regulatory compliance for risk models. Strong proficiency in Python and working knowledge of PySpark. Proficiency in building and deploying models on cloud platforms (AWS). Experience with NLP techniques is good to have Domain Ss Ability to collaborate with finance and risk teams to ensure model outputs align with business objectives and regulatory requirements. Basic understanding of credit risk management processes, including credit scoring, default probability estimation, and financial regulations. Basic working knowledge of finance and credit risk concepts, such as loan performance metrics, creditworthiness, and risk mitigation strategies. Familiarity with key financial instruments, regulatory frameworks (e.g., Basel III, IFRS 9), and their impact on risk essment models. Education and Experience Bachelor s/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. 3 to 5 years of experience in the data science and machine learning domain Experience in the financial sector or credit risk management is a bonus.
Employment Type
Full Time
Company Industry
Financial Services / Insurance Agencies and Brokerages / Investment Banking
