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Senior Data Scientist

extra holidays - extra parental leave

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

India

Offer summary

Qualifications:

Bachelor's degree in a quantitative field, 7+ years experience in data science, Expertise in applied probability and statistics, Experience building credit risk models, Proficient in SQL, Python, R, PySpark.

Key responsabilities:

Build and improve underwriting and fraud models
Derive insights from complex data sets
Apply statistical and machine learning techniques
Evaluate utility of non-traditional data sources

Motive Large https://gomotive.com/

1001 - 5000 Employees

See more Motive offers

Job description

Who we are:

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.

Motive serves more than 120,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

Visit gomotive.com to learn more.

About the Role:

We are looking for a Staff Data Scientist to build the models that power the credit risk and fraud functions for the Motive Card, a key new focus area for Motive. The Motive Card is a corporate card natively integrated with a fleet management platform, giving businesses an all-in-one solution to automate their financial and physical operations. As a member of our team you’ll help frame the problems, build models and products that win customers, and leverage machine learning at a massive scale to solidify Motive’s technology lead in the connected fleet management space.

Responsibilities:

Work closely with Risk, Product and Engineering teams to build, improve and implement underwriting and fraud models
Derive insights from complex data sets to identify credit and fraud risk
Apply statistical and machine learning techniques on large datasets
Evaluate the utility of non-traditional data sources

Qualifications:

Bachelor's degree or higher in a quantitative field, e.g. Computer Science, Math, Economics, or Statistics
7+ years experience in data science, machine learning, and data analysis - specifically in the Credit Risk space
Expertise in applied probability and statistics
Experience building credit risk and fraud models
Deep understanding of machine learning techniques and algorithms
End-to-end deployment data-driven model deployment experienc
Expertise in data-oriented programming (e.g. SQL) and statistical programming (e.g., Python, R). PySpark experience is a big plus

Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.

Please review our Candidate Privacy Notice here.

The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.

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