Bright Money is hiring for a fresher entry level Data Scientist 1 role in India

Position:

• Data Scientist I

Company:

• Bright Money

Location:

• Bangalore Urban, Karnataka, India

Job type:

• Full-time

Job mode:

• On-site

Job requisition id:

• Not specified

Years of experience:

• 0–3 years

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Company description:

• Bright Money is a fintech company with a clear mission to help Americans break free from debt using data science, artificial intelligence, and machine learning.

• It offers a mobile-first platform that integrates several personal finance tools, including automated repayment plans, budgeting solutions, credit score building, and loan refinancing services.

• The company has witnessed exponential growth in the past year, expanding its user base to more than 300,000 individuals. With over 100,000 reviews, Bright has earned the trust of customers who rely on it to simplify debt management.

• The company has secured funding from leading venture capital firms such as Sequoia, Falcon Edge, and Hummingbird, along with participation from top-tier angel investors across the United States, United Kingdom, and India. Bright has raised more than $40 million in equity funding and an additional $50 million in debt funding from Encina Lender Finance to scale its lending business.

• Positioned among the top fintech companies in the United States, Bright aims to evolve into a top 100 US financial institution by applying advanced predictive modeling to improve user outcomes. Its vision is not only to innovate financial technology but also to become the first large-scale consumer tech business built in India for global markets.

• The founding team includes leaders with deep expertise in banking, strategy, and data science, coming from organizations such as McKinsey and InMobi.

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Profile overview:

• The Data Scientist I role at Bright Money is designed for individuals who are passionate about applying advanced data science to real-world financial problems.

• The position requires a strong grasp of probability, statistics, and machine learning fundamentals to develop scalable predictive models.

• The candidate will collaborate closely with engineering, product, and business stakeholders to convert complex business problems into actionable data-driven strategies.

• Day-to-day responsibilities involve analyzing large volumes of financial transaction data, building experiments, and deriving insights that directly impact product design and customer engagement.

• The role goes beyond experimentation, requiring candidates to operationalize machine learning models and ensure that solutions are robust, scalable, and production-ready.

• Bright provides an environment where individuals can work on high-impact projects, apply the latest advancements in artificial intelligence, and see their models influence real customer experiences.

• This opportunity is ideal for individuals looking to start or grow their career in data science, especially in a global fintech context where cutting-edge methods intersect with practical financial use cases.

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Key Responsibilities:

• Apply principles of machine learning, probability, and statistics to design and refine predictive algorithms that address business challenges.

• Translate business questions into well-structured data problems, creating models that provide actionable insights for decision-making.

• Collaborate with engineers, product managers, and business teams to deploy machine learning models into live environments, ensuring accuracy, performance, and scalability.

• Conduct detailed analysis of structured and unstructured datasets, uncovering insights that drive product and business strategies.

• Implement and maintain data pipelines, ensuring data quality and consistency throughout the lifecycle of machine learning models.

• Perform continuous evaluation of model performance, fine-tuning approaches based on real-world outcomes and business needs.

• Document technical processes, including methodologies, workflows, and experimental results, to support collaboration and knowledge sharing.

• Contribute to the development of best practices for data science, including standards for experimentation, model validation, and deployment.

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Qualifications:

• A bachelor’s or master’s degree in a quantitative discipline such as computer science, mathematics, or statistics.

• Strong knowledge of key machine learning and statistical techniques, including regression, classification, clustering, hypothesis testing, and probability distributions.

• Proficiency in programming languages such as Python or R, with practical experience using machine learning libraries like scikit-learn, TensorFlow, and PyTorch.

• Understanding of tools and frameworks for deploying models into production environments, including Docker, Flask or FastAPI, and MLflow.

• Ability to design models that are not just theoretical but also practical for real-world financial use cases.

• Familiarity with modern advancements in AI and ML, such as transformers, large language models, and generative AI applications.

• Experience with cloud platforms such as AWS, Google Cloud, or Microsoft Azure is considered a plus.

• Strong communication and teamwork skills, enabling effective collaboration with technical and non-technical stakeholders.

• A results-oriented mindset with the ability to balance experimentation and practical implementation.

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Preferred Skills:

• Exposure to deep learning frameworks for advanced modeling tasks.

• Knowledge of MLOps practices including CI/CD pipelines for machine learning, monitoring, and retraining strategies.

• Practical experience with building scalable systems that integrate machine learning into user-facing applications.

• Contributions to research, publications, or side projects that showcase innovative use of contemporary AI techniques.

• Enthusiasm for applying cutting-edge data science methods to improve consumer financial products.

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What You Get to Work On:

• Analyze user behavior to create predictive models that influence customer engagement, retention, and product strategy.

• Work with large-scale financial datasets, particularly around savings account transactions, identifying patterns and opportunities to enhance customer experience.

• Apply and extend advanced models, including deep learning and large language models, to solve production-level challenges.

• Design prescriptive models that inform Bright’s debt management and financial planning tools, directly shaping user outcomes.

• Collaborate with product and engineering teams to integrate artificial intelligence into customer-facing applications, ensuring a seamless user experience.

• Experiment with new AI methodologies, such as reinforcement learning, generative models, and transformers, applying them to practical financial use cases.

• Play an active role in shaping Bright’s vision to become a leader in global fintech by leveraging India-based talent for international markets.

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Additional info:

• Bright Money emphasizes innovation, growth, and collaboration, making it a dynamic workplace for aspiring data scientists.

• Employees are encouraged to explore the latest advancements in artificial intelligence and apply them to real-world financial products.

• The role offers exposure to cutting-edge tools, frameworks, and practices in machine learning and artificial intelligence.

• Bright fosters a culture where experimentation is valued, and data-driven decision-making is central to business growth.

• Candidates joining the team will have the opportunity to contribute to a company that is rapidly scaling and positioned as one of the top fintech organizations in the United States.

• Bright’s long-term vision is not just about financial technology but about reshaping how consumers manage money and debt globally.

• With its foundation in India and focus on international markets, the company represents a unique blend of local innovation and global impact.

• This role provides a chance for early-career data scientists to be part of an ambitious journey with tangible, real-world outcomes.

Please click here to apply.