Sr. Data Scientist - Computer Vision

Role & responsibilities:

Delivery of Key Projects:

• Successfully deliver advanced analytics and data science projects within predefined timelines and budget constraints.
• Collaborate effectively with data engineers and ML engineers to comprehend data and models, utilizing various advanced analytics capabilities.

Solution Development:

• Develop efficient solutions for complex problems, showcasing expertise in handling various data types, databases, data analytics, Python programming, statistics.

End-to-End Pipeline Management:

• Manage the entire data science pipeline, including problem scoping, data gathering, modeling, insights generation, visualizations, monitoring, and maintenance.

Dashboard Design:

• Design dashboards using PowerBI or Python Dash (plotly) or Flask framework for effective data visualization and reporting.

Technological Expertise:

• Utilize CI/CD tools, data pipeline technologies, and visualization/data storytelling tools proficiently.

ETL Pipeline Building:

• Construct ETL pipelines using Python or Azure Synapse to facilitate efficient data processing and management.

Data Procurement and Management:

• Independently procure and process data, ensuring seamless integration within the company's overall data management strategy.

Technology Exploration:

• Continuously monitor advancements in artificial intelligence technology and identify applications for problem-solving within the company.

Technical Skills:

• Proficiency in

  Python

  and common libraries (

  Dash, Pandas, Scikit-Learn, Pydantic, TensorFlow, Keras, Pytorch

  ).
• Strong Knowledge in

  Statistics

  and

  Probability

  .
• Hands-on experience with

  Computer Vision

  projects.
• Set up cloud alerts, monitors, dashboards, and logging systems, troubleshoot data platform infrastructure as needed.
• Experience in

  OpenShift/Kubernetes, Azure ML

  is desirable.
• Proficiency in programming languages: Python and database query languages SQL.
• Good applied statistical skills, including hands-on experience in time series modeling, predictive modeling, distributions, regression and classification.
• Knowledge of DevOps/MLOps.
• Exceptional analytical and problem-solving skills.

Preferred candidate profile

• Bachelor's or Master's degree in Computer Science or a related technical field, or equivalent experience.
• Total of

  6

  to

  10 years

  of professional experience.
• Minimum

  4 years

  of experience in

  data science/machine learning/deep learning.

• Minimum

  2 years

  of experience with

  Computer Vision

  domain.
• Experience in DevOps, preferably with hands-on experience in one or more cloud service providers, with Azure being preferred.