Data Scientist at Kpler enhancing Gas and Power teams to aggregate data for future forecasts. Collaborating with engineers and product teams for model deployment and performance enhancement.
About the role
- Data Science/AI Manager leading analytical and AI/ML product teams for Ford's data-driven solutions. Mentoring and developing talent while ensuring high-quality technical outcomes.
Responsibilities
- Provide expert technical guidance and mentorship to data scientists & software engineers in the product team.
- Actively contribute to code reviews, design discussions, algorithm selection, and architecting scalable data science solutions.
- Lead, mentor, and develop a high-performing team of highly skilled data scientists, software engineers, and ML engineers.
- Contribute to the development and implementation of the team's innovation strategy, focusing on new product development and leveraging emerging technologies.
- Lead engagement with internal business partners and efficiently translate business requirements into data & analytical problem formulations.
- Clearly and concisely communicate technical information to both technical and non-technical audiences.
- Lead the problem formulation, research, development, and implementation of GenAI to enhance existing solutions and create new innovative applications.
- Work effectively with various teams and stakeholders to achieve business objectives.
Requirements
- Master's degree (PhD preferred) in Engineering, Data Science, Computer Science, Statistics, Industrial Engineering, or a related field.
- 5+ years of hands-on experience applying supervised and unsupervised machine learning algorithms, deep learning architectures, and statistical modeling techniques (Automotive OEM experience preferred).
- 5+ years of leading a team of cross-functional technical experts.
- Proficiency in R and Python, along with experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn, XGBoost).
- Experience with cloud-based platforms (e.g., GCP) and data related technologies (e.g., SQL, Spark, Hive).
- Strong technical & people leadership, communication, and collaboration skills.
- Understanding of business principles and critical thinking skills to translate business needs into impactful data science solutions.
- Experience with NLP, deep learning, neural network architectures, computer vision, reliability, survival analysis and anomaly detection techniques.
- Familiarity with computationally intensive statistical methods, Jira, system architecture principles.
- Google certifications on developing and deploying AI/ML models on GCP.
- Experience with various software development methodologies (Agile, DevOps), CI/CD pipelines, and testing frameworks. Proficiency in one of AngularJS, ReactJS, or any other front-end technologies.
Benefits
- Professional development opportunities.
- Health insurance.
- Flexible work arrangements.
- Paid time off.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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