Data Scientist (hybrid)

Job Title:

Data Scientist (hybrid)

Location:

Dallas, TX (Need only locals)

Duration:

Longterm

Interview Process:

Video

Note:

Coding is must.

Job Description

Strategic AI Leadership: Translate complex business challenges into clear, actionable AI/ML strategies and comprehensive technical roadmaps, ensuring alignment with organizational goals.

Team Leadership & Mentorship: Guide, mentor, and develop a high-performing team of data scientists and machine learning engineers, fostering a collaborative culture of innovation, continuous learning, and technical excellence.

End-to-End Solution Delivery: Oversee the entire machine learning lifecycle, from problem definition and data exploration to model design, training, validation, deployment, monitoring, and ongoing optimization.

Production Deployment: Lead the successful deployment of robust, scalable, and high-impact ML solutions into production environments, ensuring they generate measurable and significant business value.

Technical Excellence & Best Practices: Champion MLOps best practices, ensuring robust model governance, versioning, testing, and monitoring for all AI solutions.

Technology Evaluation & Integration: Actively research, evaluate, and integrate new AI technologies, frameworks (including Agentic frameworks), tools, and cutting-edge research findings to maintain a competitive edge and drive innovation.

Stakeholder Collaboration: Collaborate effectively with cross-functional teams, including engineering, product, and business units, to understand requirements, manage expectations, and ensure successful project delivery.

Ethical AI Development: Apply a strong understanding of ethical AI principles, fairness, transparency, and data privacy throughout the design, development, and deployment of all AI solutions..

Top Skills & Years of Experience

Qualifications:

• Experience: 8+ years of progressive experience in data science roles, with a significant focus on leading AI/ML initiatives.
  

Technical Proficiency:

• Demonstrated proficiency in Agentic frameworks (e.g., Langgraph, CrewAI), Python, and SQL.

• Deep expertise in the end-to-end ML lifecycle, including model design, training, validation, deployment, and monitoring.

• Proven experience deploying scalable ML solutions in production environments.

• Proficiency in major cloud platforms (e.g., AWS, Azure, Google Cloud Platform) for scalable AI solution development and deployment, including relevant services (e.g., SageMaker, Azure ML, Vertex AI).

• Experience with Machine Learning Frameworks such as TensorFlow, PyTorch, and Scikit-learn.

• Familiarity with data processing and manipulation libraries/tools like Pandas and Apache Spark.

• Understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model lifecycle management.

• Proficiency with version control systems, particularly Git.

• Experience with both SQL and NoSQL databases.

• Familiarity with AI/ML specific tools and platforms such as OpenAI APIs, and integration platforms like WSO2 for AI service orchestration

Recruiter Details:

Name : Ananya at gsksolutions dot com

Contact : Eight three two-Nine nine zero-Two four two seven