Data Scientist III

Purpose of the Job :

Data Scientist III leads and contributes to the development of AI solutions that drive innovation and address complex business problems. The Data Scientist III will utilize advanced technical skills and innovative problem-solving approaches to design end-to-end AI solutions, optimize models, and ensure alignment with business objectives. The focus is on leveraging expertise in machine learning, deep learning, and statistical modeling to provide valuable insights and contribute to product development. Additionally, this role involves promoting a culture of innovation, adhering to coding standards, and ensuring compliance with security and regulatory requirements in the AI domain.

Responsibilities & Accountabilities :

• Understand AI concepts and applications to solve business problems, design end-to-end AI solutions with a focus on innovation, and Utilize advanced statistical methods, machine learning, and deep learning techniques to develop and implement models, providing insights for data-driven strategies. 
• Apply complex machine learning algorithms, optimize model parameters, and handle various data challenges such as missing data and outliers to improve model performance. 
• Stay updated with the latest trends and technologies in data science, lead innovative approaches, challenge existing assumptions, and foster a culture of innovation within the team. 
• Design and implement AI solutions, considering deployment concepts like edge computing and serverless architectures, and optimize model performance through tuning and parallelization. 
• Recognize the value of automation, improve data quality through automated processes, and adhere to established guidelines for data quality assurance and validation. 
• Collaborate with different teams and stakeholders to identify opportunities for data-driven insights and innovations, fostering collaboration and sharing findings. 
• Work with unstructured data, apply natural language processing and deep learning concepts and communicate insights effectively to stakeholders with varying levels of technical understanding. 
• Align business objectives with data science goals, deeply understand target users and their needs, utilize advanced analytics to extract insights, and contribute to product metrics and success evaluation. 
• Work with various data sources, integrate structured and unstructured data, and design solutions adhering to AI security and compliance requirements. 
• Lead a team of developers and stakeholders, guide the development of complex AI solutions, and ensure timely and within-budget delivery. 
• Maintain adherence to commonly accepted coding standards and ensure effective awworkflows for data collection, cleaning, analysis, and reporting. 
• Understand and utilize cloud platforms like AWS or Azure to deploy, scale, and integrate AI solutions into existing applications or workflows. 
• Experience in streamlining processes, utilizing automation, and optimizing data-related workflows for efficiency and effectiveness. 

Performance Measurement :

• AI Solution Effectiveness: Evaluate the effectiveness of AI solutions designed and deployed, assessing their alignment with business objectives and the ability to solve complex problems. 
• Modeling Excellence: Measure the accuracy, efficiency, and optimization of machine learning and deep learning models, along with successful handling of data challenges. 
• Innovation Impact: Assess the impact of innovative approaches and solutions on addressing complex business problems and fostering a culture of innovation within the team. 
• Product Vision and Alignment: Evaluate the alignment of data science initiatives with product goals, user understanding, and successful integration of advanced analytics to extract actionable insights. 
• Process Efficiency and Automation Impact: Measure the impact of process improvements and automation on data-related tasks, including data quality, consistency, and overall workflow efficiency. 
• Cross-Functional Collaboration and Leadership: Evaluate the effectiveness of collaboration with various teams, stakeholders, and leadership in identifying opportunities for data-driven insights and successfully leading teams to deliver AI solutions. 
• Adherence to Standards and Compliance: Assess the adherence to coding standards, compliance with AI security and regulatory requirements, and best practices in data handling, quality assurance, and validation. 

Educational and Experience Requirements :

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 
• Minimum of 3-5 years of hands-on experience in data analysis, machine learning model development, and AI solution deployment. 
• Proven experience in designing and implementing end-to-end AI solutions that address complex business problems. 
• Demonstrated proficiency in machine learning algorithms, and deep learning techniques, experience in NLP and GenAI would be a plus. 
• Experience in collaborating with cross-functional teams, leading projects, and effectively communicating with stakeholders. 
• Experience aligning data science initiatives with product objectives, understanding user needs, and utilizing advanced analytics for product enhancement. 
• Experience in improving processes, implementing automation, and ensuring data quality and consistency through automated workflows. 
• Knowledge of specialized AI development tools and techniques for AI model deployment, performance tuning, and optimization. 
• Understanding of AI security and compliance requirements, ensuring solutions meet regulatory standards. 
• Proficiency in maintaining code quality, following coding standards, and adhering to best practices. 
• Proficiency in handling unstructured data, deriving insights, and effectively communicating complex analyses. 
• Demonstrated thought leadership, innovation, and a proactive approach to solving complex business problems. 
• Publications, research contributions, or teaching experience in the field of data science would be a plus.

Competencies and Behaviors :

• Display a high level of technical expertise in advanced machine learning, deep learning, statistical modeling, and data analysis. 
• Apply innovative approaches to address complex business problems, challenging assumptions, and suggesting alternative solutions. 
• Demonstrate leadership by leading projects, collaborating effectively with cross-functional teams, and fostering a culture of innovation. 
• Proficiently designed end-to-end AI solutions, considering high-level architecture, conceptual frameworks, and alignment with business objectives. 
• Possess advanced modeling skills, including the ability to optimize model parameters, handle complex data challenges, and apply various machine learning and deep learning algorithms. 
• Effectively communicate complex analyses, insights, and recommendations to stakeholders with varying technical understanding. 
• Align data science initiatives with product goals, understand user needs, and utilize advanced analytics to guide product development. 
• Recognize the value of process efficiency, automation, and data quality assurance, and apply them to streamline workflows and improve data consistency. 
• Adhere to AI security and compliance requirements, ensuring that AI solutions meet regulatory standards. 
• Display thought leadership by staying updated with the latest trends and technologies in data science and contributing innovative ideas to the team. 
• Contribute to the educational field by publishing research, sharing findings, or engaging in teaching activities related to data science. 
• Maintain code quality by adhering to commonly accepted coding standards and best practices in the field of data science. #LI-remote