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 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 Principal 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 5 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

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