Location
Bangalore | India
Job description
Job Description
Introduction
A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. With deep expertise in many industries, we offer strategy, experience, technology, and operations services to many of the most innovative and valuable companies in the world. Our people are focused on accelerating our clients’ businesses through the power of collaboration. We believe in the power of technology responsibly used to help people, partners, and the planet. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you’ll be encouraged to challenge the norm, investigate ideas outside of your role and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centres on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
Your Role and Responsibilities
- Client is looking for a Senior Data Scientist. Ideal candidate will be a highly motivated individual with a passion for driving business improvement through rigorous analysis. The role will be a combination of building on existing analytics methods and developing new methods.
- The Senior Data Scientist will report to the Head of Marketing Analytics and will support the Growth organization in data driven decisions. The role will involve direct interaction with stakeholders.
- Lead end-to-end development of machine learning models for predictive analytics, recommendation systems, and optimization problems.
- Research, design, and implement state-of-the-art deep learning models for computer vision tasks such as image classification, object detection, and image segmentation.
- Develop and optimize neural network architectures to extract meaningful features from large-scale image datasets
- Implement algorithms for classification, regression, clustering, and time series forecasting.
- Evaluate model performance using appropriate metrics and iterate on model improvements.
- Mentor junior data scientists and collaborate with cross-functional teams to deliver impactful insights and solutions.
- Conduct in-depth data analysis, explore complex datasets, and derive actionable insights to support business objectives.
- Communicate findings and recommendations to stakeholders through clear and concise presentations and reports.
- Stay abreast of industry trends and emerging technologies, and contribute to the continuous improvement of data science practices within the organization.
- Implement scalable and cost-effective solutions for data processing, storage, and model inference on GCP.
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
Required Technical and Professional Expertise
- 8 – 12 years Proven experience as a Data Scientist or a similar role, preferably in a technology or data-driven company.
- 8+ years of experience in data science, with a proven track record of delivering complex analytical solutions.
- 4+ years of hands-on experience in developing and deploying deep learning models for computer vision applications.
- Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Solid understanding of computer vision algorithms and techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).
- Strong programming skills in Python, along with experience with relevant libraries (e.g., OpenCV, scikit-image, Pandas, NumPy, SciPy).
- Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP)
Preferred Technical and Professional Expertise
- Experience with cloud computing platforms like AWS, Azure, or Google Cloud for data storage, processing, and analysis.
- Knowledge of data ethics, privacy regulations, and best practices for handling sensitive information.
- Ability to work with big data technologies and frameworks, such as Hadoop, Spark, or Kafka.
- Experience with data visualization tools like Matplotlib, Seaborn, or Tableau for communicating insights effectively.
- Familiarity with machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and natural language processing.
Job tags
Salary
