Principal Applied Scientist

Responsibilities:

• Provide strategic direction and technical leadership in applying machine learning/AI within the organization, aligned with company goals and challenges.
• Influence the R& D roadmap based on deep industry understanding and business needs.
• Drive innovation with novel solutions in the automotive industry, advancing applied science through the 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 the development lifecycle. Maintain technical excellence in algorithm development and deployment.

Requirements:

• Bachelor's/Master's/PhD in Data Science, Mathematics, Operations Research, or a 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 in a business context.
• Proficient in Machine Learning, Deep Learning and Explainable AI concepts with the ability to explain them clearly to non-technical audiences
• 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.
• Utilizing Probability and Statistics to derive meaningful insights from data.
• Proficient in deep learning frameworks like TensorFlow, Keras, and PyTorch, and utilizing computer vision (OpenCV) and natural language processing (spaCy) libraries.
• Implementing deep learning techniques, particularly Neural Networks.
• Applying both fundamental and advanced Natural Language Processing concepts. Implementing Computer Vision methodologies.
• Experience with Large Language Models is a must. Should have fine-tuned LLM on domain dataset.
• Utilizing Git for efficient code management and version control.
• Leveraging cloud platforms such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services.
• Should be well versed with Design of Experiments.
• Experience in programming with Python and SQL or similar languages.
• Experience in distributed model training.
• Proficient in data visualization and presentation, transforming complex analyses into actionable insights.
• Experience with MLOps tools and frameworks (e. g., MLflow, Kubeflow, Airflow).
• Experience using ML platforms such as Databricks and SageMaker.

Preferred Qualifications:

• Experience in Recommendation Engine, Natural Language Processing, Computer Vision.
• Domain knowledge of the automotive industry.
• Enjoys discovering and solving problems, proactively seeking clarification of requirements and direction, and being a self-starter who takes responsibility when required.
• Familiarity with Spark.
• 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.