Senior Data Scientist

Job Description: Senior Data Scientist – IBM Ecosystem Build Lab

About IBM Build Lab

The IBM Ecosystem Build Lab supports IBM's strategic partners (ISVs – Independent Software Vendors) by delivering technical expertise and facilitating the development, deployment, and market validation of joint solutions. Leveraging the power of IBM's hybrid cloud and AI platforms—including Red Hat OpenShift, IBM Cloud Paks, and the IBM Cloud and AI portfolio—the lab helps partners modernize their products to operate seamlessly across platforms. This enables partners to unlock new market opportunities, enhance their competitive edge, and join the thriving IBM partner ecosystem.

Through collaborative activities like Proofs of Concept, Minimum Viable Products, Customer-Ready Products, and Workshops, IBM Build Lab architects and developers provide essential support for cloud, data, AI, security, and more.

Your Role and Responsibilities

As a Senior Data Scientist in the IBM Build Labs team, you will play a critical role in creating and enhancing cloud applications by embedding data science workflows that generate actionable business insights. You will collaborate with ISV partners to transform their applications using IBM's cutting-edge software solutions across multi-cloud platforms.

This role will involve working closely with marketing teams, expert services, development teams, and business leaders to deliver impactful outcomes. It requires a dynamic individual who thrives in an agile environment and is passionate about enabling success for IBM and its partners.

Key Responsibilities:

• Collaborate with ISV partners to define, design, implement, and deploy machine learning (ML) technologies in their products.
• Lead partner engagements to enable and integrate IBM's Data/AI technologies into their offerings.
• Provide expertise in building, training, and deploying ML models and components.
• Capture best practices and develop technical content, such as tutorials, articles, workshops, and demos.
• Demonstrate a proactive approach to learning and implementing new technologies to enhance services.
• Lead projects involving multiple technical teams across geographies, ensuring alignment and successful execution.

Required Technical and Professional Expertise:

• Experience:

  • 8+ years in data science or data engineering, with expertise in ML model conceptualization, design, training, and deployment.
  • Proven experience in customer-facing roles (e.g., technical sales, lab services, or ISV support).

• Technical Skills:

  • Strong foundation in statistics and machine learning algorithms.
  • Expertise in Python or R for data science and familiarity with open-source libraries for NLP and Time Series.
  • Experience with ETL tools, data warehouses, and SQL.
  • Proficiency in public cloud Data/AI offerings (AWS, Azure, Google Cloud).
  • Experience with CI/CD tools like ADO or Jenkins.
  • Hands-on knowledge of IBM software solutions across multi-cloud platforms and Red Hat OpenShift.

• Other Skills:

  • Excellent written and verbal communication skills in English.
  • Ability to quickly adapt to and learn new technologies.
  • Master’s degree in Statistics or Mathematics.

Preferred Technical and Professional Expertise:

• 6+ years of experience in Big Data technologies (e.g., Hadoop, Spark).
• Expertise with Jupyter Notebooks and deep learning models using Keras.
• In-depth understanding of statistical ML models and frameworks like TensorFlow and Pytorch.
• Familiarity with IBM offerings such as Watson Studio, Watson OpenScale, and AI Fairness 360 toolkit.
• Experience in client or ISV developer advocacy.
• Certifications in Big Data technologies (e.g., Cloudera, Hortonworks, AWS, GCP, Azure).

This role offers an exciting opportunity to collaborate with IBM’s ecosystem and contribute to groundbreaking AI and data science solutions across multi-cloud environments. Join us to drive innovation, empower partners, and shape the future of AI and cloud technologies.