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Staff Data Scientist - Fleet Analytics and Modeling

  • Localização
    • Palo Alto, California
  • Agendar Full time
  • Postou

Descrição

As a Staff Data Scientist for Fleet Analytics and Modeling, you will generate timely, actionable insights for our B2B customers through retrospective analysis of fleet telemetry data. In addition, you will contribute to our real-time operations and control platform that empowers our customers to maximize productivity and minimize the cost of operating their fleets. You will assist in defining requirements for the on-going development of our data science and machine learning pipeline framework.

Responsibilities :  

  • Use data processing pipeline systems to implement workflows that enable rapid and flexible insight generation and model development at scale 

  • Work with hardware, software, and analytics teams to characterize existing fleets in terms of vehicle performance, business strategy, human behavior, and other dimensions 

  • Generate visually stunning, highly intelligible, information dense data visualizations for internal and external consumption  

  • Present results of analyses to technical team members, product team, senior management, and other stakeholders 

  • Develop robust models of fleet behavior for use in simulation, prediction, and optimization using statistical learning methods 

  • Assist in the evaluation of novel algorithmic approaches to optimize fleet logistics including advanced energy management and grid-integration of flexible loads 

  • Work with the Product team to define and innovate the deployment of more efficient, on-demand, electrified goods delivery systems 

  • Engage with cross functional teams to find opportunities to create unique, data-driven products that drive long-term engagement with our software

[Additional Description]

Required

  • Master’s degree or equivalent experience in computer science, data science, engineering, or related quantitative field

  • 5+ years of industry experience developing and deploying data-driven insights in transportation mobility systems, gaming, scientific simulation, product R&D, or related field 

  • Track record developing innovating solutions to solve complex logistical problems at scale

  • Deep experience with Python, Jupyter, Pandas, SciKit Learn, and associated tools for statistical and machine learning 

  • Experience working in teams using agile software development methodologies together with distributed version control systems (e.g., git) 


Preferred

  • Experience using big data analytics and workflow orchestration tools at scale (e.g. Databricks,DBT,UbiOps, Luigi, Airflow, Spark, etc.) 

  • Experience with A/B testing of data-driven, customer facing products 

  • Experience integrating simulation systems with distributed, data-intensive processing or analytics applications  

  • Domain knowledge in transportation and energy systems, graph algorithms, convex optimization, and/or reinforcement learning 

  • Familiarity with SQL


Desired

  • Experience designing backend data pipelines (framework selection, DAG design, etc.) 

  • Self-driven with a passion for transportation decarbonization 

  • Adherence to clean code principles 

This role is categorized as Hybrid. This means the successful candidate is expected to report onsite three times per week at minimum (Tues-Thurs.)


The compensation information is a good faith estimate only. It is based on what a successful applicant in the California Bay Area which includes the following counties: Marin, Contra Costa, San Francisco, Alameda, San Mateo, Santa Clara, and Santa Cruz might be paid in accordance with the California law.

The compensation may not be representative for positions located outside of the California Bay Area.

The annual salary range for this role is $157,800 - $241,800. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Informações sobre diversidade

A General Motors está comprometida em ser um local de trabalho que não só é livre de discriminação ilegal, como estimula verdadeiramente a inclusão e integração. Acreditamos enfaticamente que a diversidade na força de trabalho cria um ambiente no qual nossos colaboradores podem crescer e desenvolver melhores produtos para nossos clientes. Incentivamos os candidatos interessados a analisar as principais responsabilidades e qualificações de cada função e a se candidatar a qualquer cargo que corresponda a suas habilidades e capacidades. Os candidatos no processo de recrutamento podem, quando aplicável, ser solicitados a concluir com sucesso uma ou mais avaliações relacionadas à função e/ou uma seleção pré-emprego antes de iniciar o emprego.  Para saber mais, acesse Como contratamos.

Declaração de Igualdade de Oportunidades de Emprego (EUA)

A General Motors tem orgulho de ser um empregador que oferece oportunidades iguais.  Todos os candidatos qualificados serão considerados para o emprego, independentemente de raça, cor, religião, sexo, orientação sexual, identidade de gênero, origem nacional, deficiência ou status como veterano protegido. 

Adaptações (EUA e Canadá)

A General Motors oferece oportunidades a todos os candidatos a emprego, incluindo pessoas com deficiências. Se você precisa de uma adaptação razoável para ajudá-lo na sua pesquisa de cargos ou solicitação de emprego, fale conosco pelo e-mail Careers.Accommodations@GM.com ou pelo telefone 800-865-7580. No seu e-mail, inclua uma descrição da adaptação específica que você está solicitando assim como o nome do cargo e o número de requisição do cargo ao qual está se candidatando.