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Senior Data Scientist at Autofleet
Tel-Aviv, Tel-Aviv District, Israel -
Full Time

Start Date

Immediate

Expiry Date

04 Apr, 26

Salary

0.0

Posted On

04 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Optimization Algorithms, Data Infrastructure, Data Pipelines, Python, Statistical Modeling, Data Analysis, Data Visualization, SQL, A/B Testing, Simulations, Spatial Temporal Data, Time Series, Routing Optimization

Industry

Software Development

Description
Autofleet’s data scientists are responsible for researching, developing and maintaining machine learning models and optimization algorithms as well as data infrastructure and pipelines that power autofleet’s Vehicle as a Service platform for optimizing large scale fleets. As a data scientist in autofleet you will work directly with engineers, sales, product and clients in order to translate business requirements to production level prediction models and algorithms. What You’ll do Research and find creative solutions to a unique set of problems Develop and maintain machine learning models and optimization algorithms from research to production Develop data infrastructure and pipelines Collaborate with engineers, sales, product and clients Master’s/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field. Strong knowledge in Python – a must. 5+ years of hands-on experience with developing & maintaining production class Machine Learning projects aimed towards solving business problems - a must. Self-starter, fast-learner, self-motivated, able to think big and move fast. Familiarity with statistical modeling techniques. Experience in data analysis and visualization and strong knowledge in SQL. Experience with A/B testing and simulations - an advantage. Experience with spatial temporal data / time series - an advantage. Experience with routing optimization problems - a major advantage.
Responsibilities
Data scientists at Autofleet are responsible for researching, developing, and maintaining machine learning models and optimization algorithms. They collaborate with various teams to translate business requirements into production-level models and algorithms.