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Staff Data Scientist

We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world together. At Ford, were all a part of something bigger than ourselves. Are you ready to change the way the world moves? Imagine the possibilities at Ford Great ideas evolve into extraordinary products and customer experiences. When you bring passion and dedication to your job, there's no telling what you can accomplish. The Digital Manufacturing Systems team is seeking a Staff Data Scientist to help imagine, invent, and implement the technology used to manufacture the next generation of Ford vehicles. Our environment fosters product innovation, rapid iteration, and a significant amount of autonomy. Our development stack is diverse and includes a wide range of technologies, including low-level and server-side programming. Our team values fun, camaraderie, learning, and collaboration, and we are looking for someone who shares these values. We hold ourselves and our solutions to the highest standards, which we maintain through constructive code reviews, brainstorming sessions, and pair programming when appropriate. Additionally, we prioritize personal relationships and take the time to get to know each other and our partners. Sound good? We would love to hear from you. In this position The Digital Manufacturing Systems team is seeking a highly skilled and experienced Staff Data Scientist to join our growing data science team. The ideal candidate will have a proven track record of successfully designing, developing, and deploying data-driven solutions to complex business problems. This role requires strong technical skills, excellent communication abilities, and the ability to work independently and collaboratively within a team. What you'll do Lead and execute data science projects: Independently manage the entire lifecycle of data science projects, from problem definition and data acquisition to model development, deployment, and monitoring. This includes defining project scope, setting timelines, and managing resources effectively. Develop and implement advanced analytical models: Build and deploy machine learning models, statistical models, and other analytical techniques to solve business problems across various domains. This may involve a variety of techniques, including regression, classification, clustering, time series analysis, and deep learning. Data mining and analysis: Extract, clean, transform, and analyze large datasets from various sources. This involves working with SQL, NoSQL databases, and potentially cloud-based data warehouses. Develop and maintain data pipelines: Design and implement robust and scalable data pipelines to ensure efficient data flow and accessibility for analysis and model training. Collaborate with cross-functional teams: Work closely with engineers, product managers, and other stakeholders to understand business needs, define project scope, and communicate findings effectively. Strong communication and presentation skills are crucial. Mentor junior data scientists: Provide guidance and support to less experienced team members, fostering a collaborative and learning-oriented environment. Stay current with the latest advancements in data science: Continuously learn and explore new techniques and technologies to enhance the team's capabilities. Contribute to the improvement of data infrastructure and processes: Identify areas for improvement in data quality, data governance, and data infrastructure and propose solutions. You'll have PhD degree in Computer Science, Statistics, Data Science or a related field or a combination of education and equivalent work experience 10 years of experience as a Data Scientist. 5 years of programming experience in Python or R, including experience with relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch). 5 years of experience in statistical modeling, machine learning, and data mining techniques. 3 years of experience with SQL and NoSQL databases. Even better, you may have PhD degree in Computer Science, Statistics, Data Science, or a related field Experience with cloud computing platforms (Azure, GCP) Excellent communication, presentation, and collaboration skills. Ability to work independently and manage multiple projects simultaneously. Demonstrated ability to translate business problems into analytical solutions. Experience with specific industry domains (e.g., manufacturing) Experience with A/B testing and experimentation Experience with model deployment and monitoring Publication record in relevant conferences or journals Experience with data visualization tools (e.g., Steamlit) You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builderor all the above? No matter what you choose, we offer a work life that works for you, including: Immediate medical, dental, and prescription drug coverage Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up childcare and more Vehicle discount program for employees and family members, and management leases Tuition assistance Established and active employee resource groups Paid time off for individual and team community service A generous schedule of paid holidays, including the week between Christmas and New Years Day Paid time off and the option to purchase additional vacation time. For a detailed look at our benefits, click here: https://corporate.ford.com/content/dam/corporate/us/en-us/documents/careers/2024-benefits-and-comp-LL6-sal-plan-2.pdf This position is a leadership level 6 Visa sponsorship is not available for this position. Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660. LI-remote LI-LA1 Requisition ID : 38278
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What You Should Know About Staff Data Scientist, Ford Motor Company

At Ford, we believe in building not just vehicles, but a better world, and we are searching for a passionate Staff Data Scientist to join our Digital Manufacturing Systems team in Cheyenne, WY. Imagine leveraging your data expertise to drive groundbreaking innovations that will redefine how the world moves. In this role, you’ll take the reins on exciting data science projects, leading them from concept through to implementation, ensuring we harness data effectively to solve complex business problems. You’ll build advanced analytical models, employ machine learning techniques, and dive deep into data mining to extract valuable insights. Collaboration is key here at Ford, so expect to work closely with engineers and product managers to align technology with business needs. You’ll also have the chance to mentor junior data scientists, passing on your knowledge and helping to cultivate a thriving learning environment. We value your personal growth as much as our innovation, encouraging continuous learning in the ever-evolving field of data science. With a welcoming team spirit, fun, and camaraderie, you’ll feel at home as you contribute to our mission. So, if you're ready to embrace autonomy within a vibrant team, leverage the latest technologies, and shape the future of manufacturing, we can't wait to hear from you!

Frequently Asked Questions (FAQs) for Staff Data Scientist Role at Ford Motor Company
What are the responsibilities of a Staff Data Scientist at Ford?

As a Staff Data Scientist at Ford, you’ll lead and execute various data science projects, handling the entire project lifecycle from the initial problem definition through to deployment and monitoring. You'll develop and implement sophisticated analytical models to tackle business challenges, perform extensive data mining and analysis, and design scalable data pipelines. In addition, collaboration with cross-functional teams is essential, along with mentoring junior data scientists to foster a collaborative environment.

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What qualifications do I need to become a Staff Data Scientist at Ford?

To qualify for the Staff Data Scientist position at Ford, you should hold a PhD in Computer Science, Statistics, Data Science, or a related field, or have equivalent experience. You must demonstrate at least 10 years of experience as a Data Scientist, with 5 years in programming using Python or R. Familiarity with SQL and NoSQL databases, statistical modeling, machine learning, and data mining techniques is crucial for this role.

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What skills are important for a Staff Data Scientist at Ford?

Key skills for a Staff Data Scientist at Ford include expertise in machine learning, data mining, and statistical modeling. Proficiency in Python or R and experience with relevant libraries like Pandas and NumPy are vital. Strong SQL or NoSQL database skills, excellent communication abilities, and the capacity to work both independently and within a team are also necessary for this role.

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What technologies will I work with as a Staff Data Scientist at Ford?

At Ford, a Staff Data Scientist will work with a diverse technology stack, including advanced analytical models, machine learning frameworks, and various programming languages. You will also engage with SQL and NoSQL databases and possibly cloud computing platforms like Azure or GCP to aid in data analysis and model deployment.

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Is there a mentoring aspect in the Staff Data Scientist role at Ford?

Yes, as a Staff Data Scientist at Ford, you’ll have the opportunity to mentor junior data scientists. This aspect of the job is crucial as it not only helps you share your knowledge and experience but also fosters a culture of learning and collaboration within the Digital Manufacturing Systems team.

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Common Interview Questions for Staff Data Scientist
Can you explain your experience with machine learning techniques relevant to the Staff Data Scientist role?

When answering this question, provide specific examples of machine learning projects you've worked on. Discuss the algorithms you used, the challenges you faced, and how you overcame them. Highlight any successful outcomes, such as improved business metrics, demonstrating your ability to apply machine learning theory to practice.

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How do you approach data mining and analysis?

Detail your systematic approach to data mining. Explain how you identify relevant data sources, clean and preprocess your data, and analyze it to derive insights. Mention any tools or techniques you prefer, such as SQL for querying databases or specific libraries in Python for data processing, to underline your technical proficiency.

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Describe a data science project you managed end-to-end.

Share a detailed overview of a specific project, including the problem statement, the data used, and the model you developed. Explain how you defined project timelines, the resources you allocated, and your monitoring strategy post-implementation. This showcases your project management and leadership capabilities.

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What experience do you have with SQL and NoSQL databases?

Discuss your hands-on experience with both SQL and NoSQL databases. Explain the scenarios in which you've utilized each, emphasizing your ability to extract and manipulate data effectively. Highlight any relevant projects or how you've improved data access and efficiency in past roles.

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How do you ensure effective communication of your findings?

Emphasize the importance of tailoring communication to your audience, whether technical or non-technical. Describe how you incorporate data visualization tools to present complex information clearly and engage stakeholders. Highlight examples where effective communication led to actionable insights or decisions.

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Can you give an example of a time you collaborated with cross-functional teams?

Illustrate a situation where you worked with teams from different functions, such as engineering or product management. Detail your role, the challenges you faced, and how you resolved conflicts. This demonstrates your teamwork and communication skills, which are vital for success at Ford.

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What methods do you use to stay updated on advancements in data science?

Share the resources you rely on to stay informed, such as journals, blogs, online courses, or conferences. Discuss how you apply your learnings to your work at Ford, showcasing your commitment to continuous improvement and innovation in data science.

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How would you handle a situation where your model does not perform as expected?

Discuss your analytical approach to diagnosing model performance issues. Emphasize the importance of checking data quality, revisiting assumptions, and iterating on model design. This perspective highlights your problem-solving skills and resilience in overcoming challenges.

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What role does mentorship play in your work as a Staff Data Scientist?

Explain your philosophy on mentorship. Discuss how you support junior scientists through guidance, code reviews, or knowledge-sharing sessions. This portrays your leadership mindset and dedication to fostering a collaborative learning culture at Ford.

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How do you prioritize and manage multiple data science projects simultaneously?

Share your strategies for prioritization, such as understanding business impact, setting clear timelines, and breaking projects into manageable tasks. Discuss your organizational tools or methods, showcasing your ability to stay focused and efficient in a fast-paced environment.

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Full-time, hybrid
DATE POSTED
December 2, 2024

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