Principal Data Scientist

Job Summary

The Principal Data Scientist develops and implements algorithms, data analysis, and insights to drive business innovation and efficiency. This role involves leading data science projects, collaborating with cross -functional teams, and ensuring the quality and impact of data science solutions.

Responsibilities and Duties

• Lead the development and implementation of
  data science projects, including the design and development of algorithms and
  models.
  
• Collaborate with stakeholders to understand
  business requirements and translate them into data science solutions.
  
• Analyze large datasets to extract insights,
  identify trends, and support decision -making.
  
• Develop and validate predictive models,
  machine learning algorithms, and statistical analyses.
  
• Ensure the accuracy, quality, and relevance
  of data science outputs.
  
• Stay updated with the latest advancements
  in data science and machine learning, applying them to enhance solutions.
  
• Mentor and provide guidance to junior data
  scientists and other team members.
  
• Ensure compliance with data governance,
  security, and regulatory standards in all data science activities.
  
• Prepare and present data science reports
  and documentation to senior management and stakeholders.
  
• Participate in project planning and
  contribute to the development of project timelines and deliverables.
  
• Perform other duties relevant to the job as
  assigned by the Head of Data & AI Engineering or senior management.
  

Requirements

• Bachelor’s degree in Data Science, Computer
  Science, Statistics, or a related field
  
• Relevant certifications (e.g., Certified
  Data Scientist, Google Cloud Professional Data Engineer) are preferred
  
• Minimum of 8 years of experience in data
  science or related fields
  
• Experience in developing and implementing
  data science solutions for AI or technology -focused products
  
• Strong programming skills in languages such
  as Python, SQL
  
• Proficiency in data science tools and
  frameworks (e.g., TensorFlow, PyTorch, Scikit -learn)
  
• Excellent problem -solving and analytical
  skills
  
• Strong communication and interpersonal
  skills
  
• Attention to detail and commitment to
  quality
  
• In -depth understanding of data science
  principles, machine learning algorithms, and statistical analysis
  
• Familiarity with data visualization tools
  (e.g., Tableau, Power BI)
  
• Knowledge of data governance, security, and
  regulatory standards
  
• Ability to manage multiple tasks and
  prioritize effectively
  
• Strong attention to detail and commitment
  to delivering high -quality work
  
• Ability to work independently and as part
  of a team
  
• Programming languages (e.g., Python, SQL)
  
• Data science tools and frameworks (e.g.,
  TensorFlow, PyTorch, Scikit -learn)
  
• Data visualization tools (e.g., Tableau,
  Power BI)
  
• Collaboration and communication tools
  (e.g., Slack, Microsoft Teams)
  
• Data management systems (e.g., SQL, NoSQL
  databases)