Sr.Machine Learning Engineer Full-time

Intuit is seeking a Sr MLE to join our Data sciences team in Intuit India.

The Innovation team develops game changing technologies and experiments that redefine and disrupt our current product offerings. You’ll be building and prototyping algorithms and applications on top of the collective financial data of 60 million consumers and small businesses. Applications will span multiple business lines, including personal finance, small business accounting, and tax.

You thrive on ambiguity and will enjoy the frequent pivoting that’s part of the exploration. Your team will be very small and team members frequently wear multiple hats.

In this position you will have close collaboration with the different Product Group’s engineering and design teams, as well as the product and data teams in business units. Your role will range from research experimentalist to technology innovator to consultative business facilitator. You must be comfortable partnering with those directly involved with big data infrastructure, software, and data warehousing, as well as product management.

In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics. Following are the Responsibilities and Qualifications sought.

Responsibilities

• Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
• Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
• Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
• Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
• Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
• Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.