STAFF, DATA SCIENTIST

Drives the execution of multiple business plans and projects by identifying customer and operational needs; developing and communicating business plans and priorities; removing barriers and obstacles that impact performance; providing resources; identifying performance standards; measuring progress and adjusting performance accordingly; developing contingency plans; and demonstrating adaptability and supporting continuous learning. Provides supervision and development opportunities for associates by selecting and training; mentoring; assigning duties; building a team-based work environment; establishing performance expectations and conducting regular performance evaluations; providing recognition and rewards; coaching for success and improvement; and ensuring diversity awareness. Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity by training and providing direction to others in their use and application; ensuring compliance with them; and utilizing and supporting the Open Door Policy. Ensures business needs are being met by evaluating the ongoing effectiveness of current plans, programs, and initiatives; consulting with business partners, managers, co-workers, or other key stakeholders; soliciting, evaluating, and applying suggestions for improving efficiency and cost-effectiveness; and participating in and supporting community outreach events.

• Collaborate with a team of data scientists, machine learning engineers and software engineers to design, architect, build AI/ML models and systems, and deploy, operate and optimize the solutions

• Work in an Agile practice in a highly collaborative environment with a multidisciplinary team.

• Design end-to-end system architecture for GenAI/AI/ML and data intensive applications

• Mentor team of data scientists to develop their skills and business understanding

• Develop and deploy production-grade real-time/batch machine learning services

• Work with product managers to design user journeys, feedback loop and analyze user telemetry

• Identify or propose AI/ML use-cases to business teams to improve business processes and develop quick MVPs/ POCs to help stakeholders make better decisions

• Uphold a set of robust work standards to ensure we build trustworthy AI/ML solutions

• Collaborate with applied researchers and data scientists to iteratively improve our ML models and refine MLOps practice

• You have 9+ years experience in design, development, deployment, and maintenance of highly scalable, robust, and user-centric GenAI /AI /ML products and applications

• You have a bachelors/masters degree in computer science, information technology, engineering, statistics, economics, mathematics, or related area

• You have excellent industry experience in production-grade AI/ML system development with major technology companies or AI-native start-ups.

• You have extensive experience in production-grade python code development.

• You can execute our trustworthy AI/ML practice with stakeholders across the enterprise.

• You can effectively mentor junior data scientists and guide them through ambiguous technical problems on the project

• You can communicate internally and externally through publications, presentations, and other mediums on research progress, major breakthroughs, and product innovation.

• You have extensive experience with statistical analysis and programming languages e.g. Python and mainstream machine learning frameworks, e.g. TensorFlow or PyTorch.

• You have experience in building deep learning applications, neural network deployment optimizations and architecting ML systems

• You have experience in developing chatbots/ NLP/ recommendation-engine systems

• You are excited about building distributed machine learning systems at scale in production

• You are familiar with version control using Git in collaboration settings

• You have experience at writing high-performing production-quality code in Python

• You have experience in working with end-to-end CI/CD pipelines and experience with Kubernetes

• You are research driven, thorough and detail oriented

• You believe in the importance of establishing work standards and leveraging automations

• You have a history of collaboration, openness, honesty, timely decision making, and clear communication in both verbal and written forms

• You embrace lifelong learning - always learning new technologies and techniques. You are also engaged in the open-source communities to both find answers and help others

Minimum Qualifications... Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years experience in an analytics related field. Option 3: 6 years experience in an analytics or related field.