Data Scientist

Job title: Data Scientist

Company: IBM

Job description: Introduction
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk.

Your Role and Responsibilities
Our Software Networking Unit is looking for Data Scientists to join our development team to drive Artificial Intelligence & Machine Learning solutions for our data rich suite of software cloud networking products.

This role is primarily focused on developing ML solutions which leverage data from our products to drive insights and decision-making for our customers. The core responsibilities of the role involve developing and implementing machine learning and deep learning models, and executing data engineering tasks. The successful candidate will be part of our AI/ML development team who design, create, and support AI-driven products to deliver impactful AI solutions.

Your role and responsibility will encompass:

  • Developing and implementing machine learning and deep learning models to address specific business challenges.
  • Acting as data scientist and SME for our AI & ML use cases through having a good understanding of key AI & ML technologies and architectures
  • Collecting and cleansing data from diverse sources for analysis, ensuring high-quality and relevant datasets (structured and unstructured) for effective decision-making.
  • Exploring and visualizing data to uncover insights and trends, using advanced tools and techniques for meaningful data interpretation.
  • Applying statistical and mathematical techniques to analyze data, using robust analytical methods for predictive modelling and inference.
  • Establishing and upholding stringent quality benchmarks.
  • Applying your expertise in ML-Ops / AI-Ops
  • Utilizing version control for maintaining codebase integrity and collaboration, fostering a collaborative and error-free development environment.
  • Managing big data infrastructure and carrying out data engineering tasks, ensuring efficient data storage, processing, and retrieval.
  • Staying up-to-date with the latest trends and advancements in AI/ML and related technologies, and apply this knowledge to develop innovative solutions.
  • Ensuring that all solutions are developed with a focus on ethics, scalability, reliability, and performance.

Required Technical and Professional Expertise

  • 8+ years experience in AI/ML model development and evaluation with solid foundation in linear algebra, statistics & ML algorithms
  • Experience in design & development of ML models to extract insights and information from both structured and unstructured data.
  • Be familiar with automated ML models evaluation techniques.
  • Ability to design experiments to validate the feasibility and advantages of ML in different business scenarios.
  • Ability to maintain up-to-date knowledge of advances in AI & ML.
  • Be proficient in Python, with experience in coding and debugging in Python
  • Have hands-on experience with machine learning techniques and tools, including but not limited to: TensorFlow, PyTorch, scikit-learn, and XGBoost.
  • Demonstrated ability to critically assess and challenge ML models to ensure optimal performance.
  • Experience with big data technologies such as Hadoop, Spark, and NoSQL databases.
  • Fluent in written and spoken English.

Preferred Technical and Professional Expertise

  • Expertise in advanced model training methodologies including prompt tuning and fine-tuning with foundational models.
  • Familiarity in multiple programming languages (Python, Java) demonstrating versatility and adaptability is a plus.
  • Background in developing and implementing automation frameworks and strategies.
  • Certification in data engineering, machine learning, or AI.
  • Hands-on experience with a cloud computing platform such as IBM Cloud, AWS, Azure, or GCP.
  • Experience with DevOps practices and tools such as Docker, Kubernetes, and CI/CD pipelines.
  • Strong understanding of the ethical implications of AI and its applications.
  • Linux skills, preferably in RHEL
  • Experience with data visualization tools such as Tableau or Power BI.
  • Certification in data engineering, machine learning, or AI.

Expected salary:

Location: Bangalore, Karnataka

Job date: Wed, 20 Dec 2023 23:20:41 GMT

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