Sr. Data Scientist

The Sr. Data Scientist supports the development and implementation of data science projects, including the design and development of algorithms and models. This role involves analyzing large datasets, extracting insights, and collaborating with cross-functional teams to deliver high-quality data science solutions.

Responsibilities and Duties

• Support the development and implementationof data science projects, including the design and development of algorithmsand models.
• Collaborate with stakeholders to understandbusiness 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 relevanceof data science outputs.
• Stay updated with the latest advancementsin data science and machine learning, applying them to enhance solutions.
• Mentor and provide guidance to junior datascientists and other team members.
• Ensure compliance with data governance,security, and regulatory standards in all data science activities.
• Prepare and present data science reportsand documentation to senior management and stakeholders.
• Participate in project planning andcontribute to the development of project timelines and deliverables.
• Perform other duties relevant to the job asassigned by the Principal Data Scientist or senior management.
  

Requirements

• Bachelor’s degree in Data Science, ComputerScience, Statistics, or a related field
• Relevant certifications (e.g., CertifiedData Scientist, Google Cloud Professional Data Engineer) are preferred
• Minimum of 5 years of experience in datascience or related fields
• Experience in developing and implementingdata science solutions for AI or technology-focused products
• Strong programming skills in languages suchas Python, SQL
• Proficiency in data science tools andframeworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Excellent problem-solving and analyticalskills
• Strong communication and interpersonalskills
• Attention to detail and commitment toquality
• In-depth understanding of data scienceprinciples, machine learning algorithms, and statistical analysis
• Familiarity with data visualization tools(e.g., Tableau, Power BI)
• Knowledge of data governance, security, andregulatory standards
• Ability to manage multiple tasks andprioritize effectively
• Strong attention to detail and commitmentto delivering high-quality work
• Ability to work independently and as partof a team
• Programming languages (e.g., Python, R,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, NoSQLdatabases)