Data Scientist

The Data Scientist focuses ondeveloping algorithms, data analysis, and insights to drive business innovationand efficiency. This role involves working with large datasets, developingpredictive models, and collaborating with cross-functional teams to deliverdata-driven solutions.

Responsibilities and Duties

• Develop and implement data science projects, including thedesign and development of algorithms and models.
• Collaborate with stakeholders to understand businessrequirements 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 learningalgorithms, and statistical analyses.
• Ensure the accuracy, quality, and relevance of data scienceoutputs.
• Stay updated with the latest advancements in data scienceand machine learning, applying them to enhance solutions.
• Provide support and guidance to other team members asneeded.
• Ensure compliance with data governance, security, andregulatory standards in all data science activities.
• Prepare and present data science reports and documentationto senior management and stakeholders.
• Participate in project planning and contribute to thedevelopment of project timelines and deliverables.
• Perform other duties relevant to the job as assigned by theSr. Data Scientist 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 3 years of experience in data science or relatedfields
• Experience in developing and implementing data sciencesolutions for AI or technology-focused products
• Strong programming skills in languages such as Python, R, orSQL
• 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, machinelearning algorithms, and statistical analysis
• Familiarity with data visualization tools (e.g., Tableau,Power BI)
• Knowledge of data governance, security, and regulatorystandards
• Ability to manage multiple tasks and prioritize effectively
• Strong attention to detail and commitment to deliveringhigh‑quality work
• Ability to work independently and as part of 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, NoSQL databases)