Lead Data Science Engineer for AI Pipeline Development

2 days ago

Islamabad, Islamabad, Pakistan beBee Careers Full time

We are seeking a highly skilled Lead Data Science Engineer to join our team and lead the development of AI pipelines for diverse projects.

About the Role

This individual will play a key role in identifying and addressing issues within the pipeline, while maintaining performance analytics to ensure optimal functionality.

Key Responsibilities
  • Leverage AI pipelines to process data according to project requirements, ensuring efficient and effective data analysis.
  • Analyze geospatial data using GIS software like QGIS and ArcGIS, providing valuable insights into complex spatial relationships.
  • Troubleshoot issues within AI pipelines, including data quality problems, algorithmic errors, and performance bottlenecks, to ensure seamless system operation.
  • Track key metrics, create dashboards, and analyze data to optimize efforts and drive business growth.
  • Provide technical guidance and support to team members on AI pipeline usage and maintenance, fostering a culture of collaboration and knowledge sharing.
  • Emphasize strong communication and collaboration skills for effective cross-functional teamwork, ensuring that all stakeholders are informed and aligned.
  • Oversee multiple projects, prioritize tasks, and meet deadlines consistently, demonstrating exceptional organizational and time management skills.
  • Continuously learn and adapt to the latest developments in AI and data analytics, staying ahead of the curve and driving innovation.
  • Ensure adherence to data security and compliance standards, protecting sensitive information and maintaining the highest level of confidentiality.
Requirements

Necessary Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 2+ years of experience in the field, with a proven track record of success.
  • Proficiency in SQL and Python for data analysis, with experience using Pandas, NumPy, Matplotlib, Geopandas, and Shapely.
  • Experience in geospatial data analytics, including QGIS, ESRI products, and ArcGIS, with a strong understanding of spatial relationships and patterns.
  • Strong analytical and problem-solving skills to diagnose complex technical challenges, with a creative approach to finding solutions.
  • A detail-oriented approach to ensure high-quality deliverables, with a focus on accuracy and precision.
  • Experience in performance analytics and deriving insights from data, with a ability to communicate complex findings to non-technical stakeholders.
  • Knowledge of the Transportation Infrastructure Ecosystem and Asset Management is an advantage, but not required.
  • Certifications in AI, data analytics, or related fields are a plus, demonstrating expertise and commitment to ongoing learning.

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