Job Details
Company Overview:
Voyager Global Mobility and its subsidiaries play a central role in urban transportation in some of the most dynamic cities throughout the Americas. We power more than 10,000 drivers with professionally managed vehicles and resources so they can succeed as entrepreneurs in the ride-sharing economy. Our fleet-as-a-service model a scalable infrastructure of well-maintained vehicles, driver resources, data, and metrics can be deployed to empower the Uber platform and other noted rideshare services to deliver world-class service anywhere.
Job Description:
We are seeking a dynamic leader for data science projects, responsible for planning, execution, and delivery within set timelines and budgets. Key duties include defining project scope, providing team leadership, applying advanced statistical techniques, ensuring data quality, and fostering stakeholder engagement. Strong technical proficiency and communication skills are required. Bachelor's degree in a quantitative field and 5+ years of experience in data science or related fields preferred.
Essential Job Functions:
Project Management:
- Lead the planning, execution, and delivery of data science projects within defined timelines and budgets.
- Define project scope, objectives, and deliverables in collaboration with stakeholders.
- Develop project plans, allocate resources, and track progress to ensure successful completion.
Team Leadership:
- Provide leadership and guidance to a team of data scientists, analysts, and engineers.
- Foster a collaborative and innovative team culture, encouraging knowledge sharing and professional development.
- Mentor team members, provide feedback, and facilitate their growth and career progression.
Technical Expertise:
- Apply advanced statistical and machine learning techniques to analyze large datasets and extract valuable insights.
- Develop predictive models, algorithms, and data-driven solutions to address business challenges and opportunities.
- Stay abreast of the latest developments in data science, machine learning, and AI technologies, and evaluate their potential for application in the organization.
Data Governance and Quality:
- Establish and enforce data quality standards, best practices, and governance processes to ensure the reliability and integrity of data assets.
- Collaborate with data engineers and architects to design and implement robust data pipelines and infrastructure for data acquisition, storage, and processing.
Stakeholder Engagement:
- Collaborate closely with business stakeholders to understand their requirements, priorities, and pain points, and translate them into data-driven solutions.
- Communicate findings, insights, and recommendations effectively to non-technical audiences through visualizations, reports, and presentations.
Cross-functional Collaboration:
- Work closely with cross-functional teams, including product management, marketing, operations, and IT, to identify opportunities for leveraging data science to drive business value.
- Collaborate with software engineers and IT professionals to integrate data science solutions into existing systems and applications.
Continuous Improvement:
- Continuously assess and improve data science processes, methodologies, and tools to enhance efficiency, scalability, and effectiveness.
- Conduct post-mortem analyses and lessons-learned sessions to identify areas for improvement and implement corrective actions.
- Perform other duties as assigned.
- Must be able to work with or without reasonable accommodations.
Education Requirements:
A bachelor's degree in a quantitative field such as Computer Science, Mathematics, Statistics, Engineering, or a related field. A master's degree or higher is a bonus.
Qualifications Needed:
- 5+ years of experience in data science, machine learning, or related fields, with a proven track record of leading successful data science projects from inception to delivery.
- Demonstrated experience in applying advanced statistical and machine learning techniques to solve real-world problems and drive business value.
- Experience in leading and mentoring a team of data scientists, analysts, or engineers preferred, not required.
- Strong project management skills, including the ability to prioritize tasks, manage resources, and deliver results within tight deadlines.
- Strong knowledge of statistics, mathematics, and computer science fundamentals.
- Proficiency in programming languages commonly used in data science, such as Python, R, or SQL.
- Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/seaborn.
Technical Skills Required:
- Proficiency in data manipulation and analysis using libraries such as pandas, NumPy, or dplyr.
- Experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch.
- Familiarity with big data technologies and distributed computing platforms such as Hadoop, Spark, or AWS EMR.
- Knowledge of data warehousing concepts and tools such as AWS Redshift, Google BigQuery, or Snowflake.
- Experience with version control systems such as Git and collaborative development workflows.
Soft Skills Required:
- Excellent communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.
- Strong leadership and interpersonal skills, with the ability to motivate and inspire team members and foster a collaborative team environment.
- Analytical mindset with a keen attention to detail and a passion for solving challenging problems.
- Adaptability and willingness to learn new technologies and methodologies in a fast-paced, dynamic environment.
Preferred Qualifications:
- Experience in a specific industry or domain such as fleet management, finance, or e-commerce.
- Certifications in relevant areas such as data science, machine learning, or project management (e.g., Google Cloud).
- Experience with natural language processing (NLP), computer vision, or other specialized areas of machine learning.
- Familiarity with agile development methodologies and tools such as Agile.
- Contributions to the data science community, such as publications, conference presentations, or open-source projects.
Benefits:
- Competitive salary of $140k with an annual discretionary bonus
- Full Benefits package
- Company holidays, sick, and personal time
The Company reserves the right to modify essential job functions, qualifications and overall job duties at any time in order to support the needs of the business. Any changes will be communicated to the appropriate parties.