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Cadre

Staff Data Scientist

Cadre, San Francisco, California, United States, 94199


Staff Data Scientist

San Francisco, California, United States

Who We Are

Baton is seeking ambitious individuals who desire the autonomy and agility of a startup environment combined with the backing, power, reach, and stability of a highly respected logistics industry giant.

Baton is the Silicon Valley-based technology innovation lab for Ryder, a leading logistics company that owns 260k trucks and manages $7.4B of freight.

Prior to the September 2022 acquisition, Baton was a venture-backed start-up that operated a fleet of trucks and hung out at truck stops to truly understand the challenges at hand.

The Problem We're Solving

Our mission is to eliminate supply chain waste by creating a digital platform to manage freight and eliminate supply chain waste.

There are 500 million hours wasted in trucking each year, over 3 billion gallons of fuel wasted per year from trucks idling, and 1 in 5 trucks on the road driving empty at any given point. This has a massive impact on the environment, the lives of millions of drivers, and ultimately, the cost of goods that we all pay. Baton is fixing that, and you will too through the impactful work you'll do here.

Location Hayes Valley, San Francisco, CA

Office days: Tuesday, Wednesday, Thursday

Work from home days: Monday and Friday

Job Description

We are seeking a skilled Staff Software Engineer, Data Scientist to lead data science projects, develop machine learning models, and perform in-depth data analysis. This role involves building and deploying models for applications like demand forecasting and route optimization, conducting data wrangling, and applying statistical methods to derive insights.

Collaboration with cross-functional teams and continuous learning to stay updated with the latest trends in data science are essential for success in this role. Excellent communication skills are required to present complex data insights to non-technical stakeholders and work effectively in a collaborative team environment.

The ideal candidate will have advanced proficiency in Python, strong SQL skills, experience with machine learning frameworks, and a solid background in statistical analysis and data-driven decision-making.

Responsibilities

Lead Data Science Projects:Lead the design, development, and implementation of machine learning models and advanced analytics solutions to solve complex business problems.Data Analysis and Visualization:Perform in-depth data analysis using statistical techniques and create insightful visualizations to communicate findings to stakeholders.Machine Learning Model Development:Build, test, and deploy machine learning models for various applications, such as demand forecasting, route optimization, and predictive maintenance.Data Manipulation and Cleaning:Conduct data wrangling and preprocessing to ensure data quality and integrity, using tools like Pandas and NumPy.Statistical Analysis:Apply statistical methods, including hypothesis testing and inferential statistics, to derive actionable insights from data.Collaboration and Communication:Work closely with cross-functional teams, including engineering, operations, and business units, to understand their needs and deliver data-driven solutions.Present complex data insights in a clear and concise manner to non-technical stakeholders.Continuous Learning:Stay updated with the latest trends and technologies in data science and actively contribute to a culture of continuous improvement and innovation.Required Qualifications

Production Python Expertise:Advanced proficiency in PythonData Analysis Expertise:Deep understanding of data analysis techniquesAbility to derive actionable insights from large data setsMachine Learning & Statistics Expertise:Substantial knowledge in machine learning algorithmsStatistical methods to develop predictive models and analytics toolsPreferred Qualifications

Experience:5-7 years of experience in data science, with a proven track record of leading and delivering complex data projects.First Principles Thinking:Break down complex problems into their most basic elements and reconstruct solutions from the ground upProblem-Solving Skills:Excellent critical thinking and problem-solving abilities, with experience in formulating data-driven solutions to business challenges.Education:Master's or PhD in Data Science, Computer Science, Statistics, or a related field.Communication Skills:Outstanding verbal and written communication skills, with the ability to present complex data insights to a non-technical audience.Collaboration:Proven ability to work effectively in a collaborative team environment and manage multiple projects simultaneously.Technical Skills:Advanced proficiency in PythonStrong SQL skills for data manipulation and queryingMachine learning frameworks: Scikit-Learn, TensorFlow, Keras, and PyTorchProficiency in data visualization toolsFamiliarity with cloud platforms like AWSThe Perks

Competitive salary and bonus structureAnnual bonus and Long Term Incentive Plan participationHybrid work schedule401k with matchingMedical, Dental, and Vision health coverageEmployee Stock Purchase Program (15% discount to market value)Hyper-stable, publicly traded enterpriseCollaborative, fun, and tech forward office in Hayes Valley (San Francisco)Compensation will vary based on factors including skill level, proficiencies, transferable knowledge, and experience. In addition to base salary, Baton's full-time employees are eligible for an annual performance bonus.

Why You Should Join

Have an immediate impactWith Ryder's existing customer base of 50,000+ companies and an internal headcount of 43,000, the scale and impact of our products will be large and far-reaching, from day one.Opportunity to grow and lead in a Fortune 500 companyYou'll get to work in a rapidly growing, startup-like environment while having the stability and backing of Ryder and its full executive team.Creative, fast-paced environment to solve impactful problems in supply chainWe're going to design completely new tools for an industry that hasn't been rethought in decades. And to do this, we need people who think differently.