About the role

Senior Data Scientist

Job Summary:

The Senior Data Scientist will leverage strong business acumen to identify and define business problems while developing and testing hypotheses that inform impactful solution designs. With expertise in customer sentiment analysis and advanced AI/ML methodologies, this role is pivotal in deriving meaningful insights and driving business value through technology.

Key Responsibilities:

Develop high-quality code using Python for machine learning applications.
Collaborate with Engineers and Product Managers to formulate hypotheses, solutions, and desired outcomes.
Serve as a Subject Matter Expert on ML, Data, and AI statistical models to address complex business challenges.
Implement advanced models in Machine Learning, Optimization, Neural Networks, and Artificial Intelligence including Natural Language Processing.
Employ Data Engineering techniques to gather, prepare, cleanse, and transform data for analysis and AI automation, including creating efficient data pipelines.
Extract and analyze data from various social media platforms like Twitter, Instagram, Reddit, and Facebook to inform business strategies.
Create prototypes and minimally viable products to demonstrate innovative solutions and insights.

Requirements:

10+ years of hands-on experience as a Data Scientist with deep expertise in Machine Learning and AI algorithms.
5+ years of experience utilizing ML frameworks such as TensorFlow, PyTorch, and Keras.
4+ years of coding experience in languages such as Python, R, Scala, or Go.
Strong familiarity with source control systems like Git for version management.
Proven experience in delivering meaningful insights and demonstrating business value from analytical findings.
Ability to mentor and coach team members in Data Science approaches and methodologies.
Excellent communication skills to convey complex insights to stakeholders effectively.

Preferred Qualifications:

Experience in prompt engineering, RAG system setup, and microservices architecture using container technologies such as Docker and Kubernetes.
Familiarity with deploying and maintaining services in Kubernetes environments.
Hands-on experience with AWS services, including SageMaker, Comprehend, Lex, Rekognition, and others.
Experience troubleshooting production systems to maintain performance and reliability.
Good understanding of and experience with CI/CD systems such as Jenkins and GitLab for automated deployment processes.

Benefits:

Competitive salary with performance-based bonuses.
Comprehensive health, dental, and vision insurance.
Flexible work hours and remote work options to promote work-life balance.
Professional development opportunities and access to training resources.
Collaborative and inclusive company culture fostering innovation.
Retirement savings plan with company match to support long-term financial goals.
Generous paid time off policy, including vacation days, sick leave, and holidays.

AIML Lead