MSMEs contribute significantly to India’s total GDP. 90% of India’s ~$1 Trillion Retail Market is controlled by Micro, Small & Medium Enterprises (MSMEs). Which means ~$900B worth of commerce flows through these ~60M MSMEs in the form of shops/kiosks/homes, scattered all over the country.We at Khatabook, have a vision to empower MSMEs and help them increase their incomes. We have built a product that brings efficiency in MSME operations by providing them easy to use tools to manage their receivables, inventory and billing which creates transparency in their cash flow. Within the Khatabook platform, we have also enabled the facility to take loans for their short term working capital needs for select Khatabook users that are displaying good credit behavior. Our app has been downloaded over 100 Million times with a monthly active user base of 8 Million+ which are adding 220 Million+ transactions with a transaction value of $18 Billion.
People are our biggest asset! At Khatabook, every one of us is a dynamic superstar. We have carefully bred an ecosystem which hires nothing but incredibly and exceptionally talented people who can dream, collaborate, experiment, and break new ground. We’re a strong team that looks out for each other.
We, at Khatabook are looking to hire a Data Scientist II. If you want to tackle hard and interesting problems at scale and create an impact within an entrepreneurial environment, this is the place for you.
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Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
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Mine and analyze data from company databases to drive optimisation and improvement of product development, marketing techniques and business strategies.
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Assess the effectiveness and accuracy of new data sources and data gathering techniques.
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Develop custom data models and algorithms to apply to data sets.
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Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
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Develop company A/B testing framework and test model quality.
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Coordinate with different functional teams to implement models and monitor outcomes.
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Develop processes and tools to monitor and analyze model performance and data accuracy.
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2+ years of experience manipulating data sets and building statistical models.
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Strong problem-solving skills with an emphasis on product development.
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Experience using statistical computer languages (R, Python, SQL, etc. ) to manipulate data and draw insights from large data sets.
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Experience working with and creating data architectures.
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Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc. ) and their real-world advantages/drawbacks.
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Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc. ) and experience with applications.
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Experience in working with a full ML project lifecycle: understanding the problem statement and data, feature creation, development, tuning, validating, deployment, monitoring and retraining.
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Excellent written and verbal communication skills for coordinating across teams.
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Knowledge of real-time and batch deployment techniques.
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Worked with MLOps pipeline and tools such as GIT, DVC, S3, Airflow and Kubernetes
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A drive to learn and master new technologies and techniques.
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Bachelor's degree in Statistics, Mathematics, Computer Science or another quantitative field
