Director, Data Science

Job Details:

Job Description:

Join Altera, a leader in programmable logic technology, as we strive to become the #1 FPGA company. We are seeking a strategic and technically proficient Director of Data Science to lead the development, deployment, and governance of enterprise-wide AI and machine learning solutions. This role is central to our Data & Analytics team and will define how we leverage AI/ML across the business, from ideation to production.

You will be responsible for architecting robust, scalable, and secure ML pipelines using a modern toolset, with a strong emphasis on Microsoft Azure services. As a senior leader in this space, you will also drive MLOps best practices, mentor technical teams, and ensure AI initiatives align with both business priorities and ethical standards.

Responsibilities

• Define and execute the AI/ML strategy across business domains, collaborating with senior stakeholders to identify high-impact use cases.

• Design and implement robust AI/ML solutions using tools like Azure Machine Learning, Dataiku, and Kubeflow pipelines,etc., ensuring scalability, reproducibility, and performance.

• Build and manage full-lifecycle ML pipelines from data ingestion and training to deployment and monitoring using tools like Azure ML, Kubeflow, and Dataiku, etc.

• Establish MLOps practices including versioning, CI/CD for models, automated testing, and model drift monitoring.

• Work closely with data engineers, business analysts, product teams, and domain experts to translate complex business problems into ML-driven solutions.

• Integrate solutions with enterprise tools, leveraging widely-used libraries and platforms (e.g., TensorFlow, PyTorch,etc.) and APIs for NLP, computer vision, and generative AI (e.g., Azure OpenAI, Cognitive Services).

• Ensure AI solutions are explainable, reproducible, and aligned with enterprise data governance and ethical AI principles.

• Provide technical guidance to junior ML engineers and data scientists; establish reusable components and share best practices across teams.

• Stay ahead of industry trends and continuously evaluate emerging tools and technologies that can enhance AI delivery at scale.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, Engineering, or a related field.

• 15+ years of experience in building and deploying machine learning models in enterprise environments.

• Deep expertise in the Azure AI/ML ecosystem, especially:

  • Azure Machine Learning (AutoML, ML Designer, SDK)

  • Azure Synapse Analytics and Data Factory

  • Azure Data Lake, Azure Databricks

  • Azure OpenAI and Cognitive Services

• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, etc.

• Strong understanding of MLOps, containerization (Docker/Kubernetes), and CI/CD pipelines using Azure DevOps or GitHub Actions.

• Hands-on experience with Dataiku and/or Kubeflow for collaborative modeling and production workflow orchestration.

• Demonstrated ability to design ML architectures that meet performance, scalability, and security standards.

• Experience working with structured, unstructured, and semi-structured data across business or industrial domains.

• Experience with real-time analytics, streaming data, or IoT use cases.

• Communication, leadership, and strategic planning skills.

• Understanding of semiconductor industry processes and business requirements.

Why Join Us

• Drive enterprise-wide AI transformation in a data-forward organization.

• Work with a modern Azure-centered data stack.

• Collaborate with cross-disciplinary teams to solve real-world problems with AI.

• Lead innovation in a supportive environment that values experimentation and impact.

Job Type:

Regular

Shift:

Shift 1 (India)

Primary Location:

Ecospace 1

Additional Locations:

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.