Pune, Maharashtra, India
Finance & Banking
Full-Time
Vyapar
Overview
About Vyapar:
We are a technology and innovation company in the fintech space, delivering business accounting software to Micro, Small & Medium Enterprises (MSMEs). With more than 10 Million users across 140 countries, we are one of the fastest growing companies in this space. We take the complexity out of invoicing, inventory management & accounting, making it so simple, such that small businesses can spend less time on manual bookkeeping and spend more time focusing on areas of business that matter.
Role Summary:
Vyapar’s Data team builds the technology platform that eases and digitizes our customers' bookkeeping and enables the transition of cumbersome accounting data from general bookkeeping to a digitized always available resource.
As a key member of Vyapar's Data team, you will play a pivotal role in building the technology platform that revolutionizes our customers' bookkeeping processes. Leveraging your expertise in Machine Learning (ML) and Generative Artificial Intelligence (AI), you will lead the development and implementation of innovative solutions aimed at digitizing and streamlining accounting data. Collaborating closely with cross-functional teams, you will gather requirements, design advanced ML and AI models, analyze data, and deploy solutions. Your contributions will drive business growth, enhance efficiency, and foster innovation, ensuring Vyapar remains at the forefront of the fintech industry.
Key Responsibilities:
- Conducting research on cutting-edge ML and AI techniques to innovate data analysis, predictive modeling, and optimization.
- Designing, developing, and implementing ML and AI models to tackle specific business challenges, employing various statistical and machine learning methods like regression, classification, clustering, and deep learning.
- Analyzing vast, intricate datasets for valuable insights through exploratory data analysis and visualization, understanding data trends and characteristics.
- Evaluating model performance using relevant metrics and validation techniques, optimizing parameters to enhance accuracy and generalization.
- Collaborating with diverse teams including data engineers, software developers, and business stakeholders, effectively communicating technical concepts to both technical and non-technical audiences.
- Deploying ML and AI models in production environments with a focus on scalability, reliability, and performance, seamlessly integrating them with existing systems for real-time decision-making.
- Continuously updating knowledge in ML, AI, and related fields, fostering a culture of innovation and excellence by sharing best practices within the team.
Desired Skills And Requirements:
Must have
- Programming Languages Python/ R, PySpark.or Java
- Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and libraries commonly used in NLP and Generative AI.
- Hands-on experience with Deep Learning Technology.
- Expert level understanding of statistical analysis, ML algorithms, and data modeling techniques.
- Experience in the application of Linear Programming and metaheuristic algorithms of Artificial Intelligence.
- Familiarity with Data Visualization Tools such as Tableau, Power BI, Data-Driven Documents.
- Solid understanding of A/B testing principles to refine and optimize models.
- Strong problem-solving skills, critical thinking abilities, and attention to detail.
- Effective communication and collaboration skills with the ability to work in a fast-paced, dynamic environment.
- Exposure to solving use cases using Generative AI
- Exposure to Reinforcement Learning algorithms
Good to have
- Cloud platforms e.g., AWS, Azure, GCP
Experience:
- Proven experience of 1-3 years working as a Data Scientist or similar role, with a focus on Machine Learning, NLP and Generative AI.
- Must have one year of experience in Python / R.
- Experience working with real-world datasets in domains finance, e-commerce, etc.
- Product Company background is a plus.
Education:
- Bachelor’s or Master’s degree in computer science, Data Science, Statistics, Mathematics, or a related field.
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