Spearhead the design, development, and deployment of ML and NLP models, ensuring they align with product objectives and goals.
Collaborate with cross-functional teams, particularly product managers and engineers, to integrate models into product offerings and optimize their performance post-deployment.
Translate complex datasets into actionable insights, using advanced statistical methodologies to improve product features and drive user engagement.
Provide expertise in data exploration, feature engineering, and model validation, ensuring the highest standards of accuracy and efficiency.
Utilize cloud platforms and tooling to facilitate seamless data integration, model training, and analysis at scale.
Mentor and guide junior data scientists and analysts, establishing best practices and promoting continuous learning within the team.
Introduction As a Data Scientist at IBM, you will help transform our clients' data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it's investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.
Required Technical and Professional Expertise
Master's Degree in Computer Science, Data Science, Statistics, or related field.
7+ years of hands-on experience in ML and NLP model development, deployment, and post-deployment optimization.
Demonstrable proficiency in key statistical methods and their practical application to real-world product challenges.
Proficient in Python and its associated data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn, NLTK, spaCy).
Experience with cloud platforms (e.g., AWS, GCP, Azure) and their data analysis tools (e.g., BigQuery, Redshift, Data Lake).
Proven ability to work in tandem with product teams, translating data insights into actionable product enhancements.
Preferred Technical and Professional Experience
Ph.D. in a related field.
10+ years of applied data science experience, with a significant focus on product-centric roles.
Comprehensive understanding of cloud tooling and architectures specifically tailored for data analysis and ML workloads.
Hands-on experience with deploying ML and NLP models at scale, ensuring their robustness and efficiency in a product environment.
Familiarity with CI/CD practices, especially as they pertain to the deployment and updating of ML models.
Strong communication skills, with the ability to convey complex data-driven insights to non-technical stakeholders.
Demonstrated leadership qualities, with prior experience in mentoring or leading data science teams.
Proactive in staying updated with the latest advancements in ML, NLP, and cloud technologies, ensuring their effective adoption within the team and products.
Required Education Bachelor's Degree
Preferred Education Bachelor's Degree
About Business Unit IBM Software infuses core business operations with intelligence-from machine learning to generative AI-to help make organizations more responsive, productive, and resilient. IBM Software helps clients put AI into action now to create real value with trust, speed, and confidence across digital labor, IT automation, application modernization, security, and sustainability. Critical to this is the ability to make use of all data, because AI is only as good as the data that fuels it. In most organizations data is spread across multiple clouds, on premises, in private datacenters, and at the edge. IBM's AI and data platform scales and accelerates the impact of AI with trusted data, and provides leading capabilities to train, tune and deploy AI across business. IBM's hybrid cloud platform is one of the most comprehensive and consistent approach to development, security, and operations across hybrid environments-a flexible foundation for leveraging data, wherever it resides, to extend AI deep into a business.
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