Senior Staff, Applied Science

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Tekion is looking for an experienced Applied Scientist to help shape the future of Automotive Industry. At Tekion we transform the end-to-end
experience of customers in automotive. Candidate should be a self-starter, comfortable with ambiguity, have an affinity for building things
from scratch, demonstrate strong attention to detail, and have the ability to work in a fast-paced, complex and ever-changing environment.
You'll be able to bring your unique skills and expertise to shape the direction of our Machine Learning team. You will have an opportunity to
work with state of art machine learning algorithms on large datasets.
We are looking for highly motivated applied scientists interested in delivering the next level of innovation for Tekion.

Core Responsibilities:
Provide strategic direction and technical leadership in applying machine learning/ AI within the organization, aligned with company goals and challenges. Influence R&D roadmap based on deep industry understanding and business needs. Drive innovation with novel solutions in the automotive industry, advancing applied science through latest research implementation. Act as a key liaison between R&D and stakeholders, ensuring technical alignment with business objectives. Collaborate with cross-functional teams to define and integrate machine learning solutions into products and services. Publish research in top conferences, advancing field knowledge. Provide mentorship to applied scientists, ensuring project success.Contribute to team growth through training and collaborative projects. Define metrics for model evaluation in offline and real-time settings. Quantify and communicate ML impact to executives, influencing
decisions. Champion ethical AI practices, ensuring compliance and standards. Define best practices for ML model development, testing, validation, and monitoring. Demonstrate data-driven business acumen and technical expertise across development lifecycle. Maintain technical excellence in algorithm development and deployment.

Technical Skills
Candidate should be proficient in SQL and Python, with familiarity in Spark considered advantageous. The ideal candidate will demonstrate expertise in:
1. Proficient in Machine Learning, Deep Learning and Explainable AI concepts with the ability to explain them clearly to non-technical audiences
2. Experienced in developing and adapting state-of-the-art models for specific business needs, demonstrating a track record of success in complex, cross-functional projects.
3. Utilizing Probability and Statistics to derive meaningful insights from data.
4. Proficient in deep learning frameworks like TensorFlow, Keras, and PyTorch, and utilizing computer vision (OpenCV) and natural
language processing (spaCy) libraries.
5. Implementing deep learning techniques, particularly Neural Networks.
6. Applying both fundamental and advanced Natural Language Processing concepts.
7. Implementing Computer Vision methodologies.
8. Experience with Large Language Models is a must. Should be able to write precise prompts covering multiple aspects of the intended tasks.
9. Utilizing Git for efficient code management and version control.
10. Leveraging cloud platforms such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services.
11. Should be well versed with Design of Experiments.

Required Qualifications :
Bachelors/ Masters / PhD in Data Science, Mathematics, Operations Research or related field. The right candidate has a background
in probability and statistics, applied mathematics, or computational science and a history of solving difficult problems with good business
impact using a scientific approach.
Experience working with major ML algorithms and frameworks.
Significant experience in Data Science and Machine Learning with a strong proven track record in delivering positive business impact.
12+ years of hands-on experience with analytics, data science and big data experience in a business context.
Experience in programming in Python or similar languages.
Experience with data visualization and presentation, turning complex analysis into insights.

Preferred qualifications
Experience in Recommendation Engine, Natural Language Processing.
Domain knowledge of automotive industry.
Enjoys discovering and solving problems; proactively seeking clarification of requirements and direction; being a self-starter who takes
responsibility when required.
Strong interpersonal, verbal, visual and presentation skills, ability to communicate complex findings in a simple manner to executives.
Ability to work collaboratively across multiple products and application teams.
A willingness to learn, share and improve.

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics. 

For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

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