Data Scientist at Hitachi Careers

Posted 6 months ago
Bengaluru, Karnataka
Application deadline closed.

Job Description

Data Scientist

Hitachi Careers


Duties and Responsibilities
• Research and Develop Innovative Use Cases, Solutions and Quantitative Models in support of Hitachi’s cross-industry business needs like Energy, Industry, Mobility, Smart Life, and Information Technology.
• Design, Implement and Demonstrate Proof-of-Concept and Working Proto-types for Hitachi and its clients.
• Provide R&D support to Hitachi business units and group companies to productize research prototypes.
• Explore emerging tools, techniques, and technologies, and work with academia for cutting-edge solutions.
• Collaborate with cross-functional teams and eco-system partners for mutual business benefit.
• Generate eminence via patents, publications, thought leadership, invited speakerships and conspicuous presence in forums of repute.
• Add value to self through continuous learning and knowledge acquisition.
• Give back learnings to colleagues and communities.

Mandatory Requirements

Academic Qualification:

Bachelor’s degree with STEM… background (Science, Technology, Engineering and Management) with strong quantitative flavour.

Strong Fundamentals: The candidate is required to build quantitative models from first principles and hence need to have excellent understanding of basics in mathematics and statistics (e.g., differential equations, linear algebra, matrix, combinatorics, probability, Bayesian statistics, eigen vectors, Markov models, Fourier analysis).

Application Domain: The candidate is expected to specialize in any one of the following
• Predictive Analytics, Time Series Analysis and Forecasting
• Prescriptive Analytics and Mathematical Optimization
• Exploratory Analytics and Simulation (Discrete-event, Monte-Carlo)
• Computer Vision and Image Processing
• Speech and Audio Signal Processing
• Natural Language Processing
• Multi-Modal Analytics and Sensors

It is required to have hands-on model implementation skills for any one of the above areas using any widely used technology stack (e.g., Python/Tensor Flow/OpenCV/Keras, Apache Spark/Scala/Java, R, SAS, RapidMiner, Azure, SageMaker, Watson)

Emerging Trends – Artificial Intelligence and Machine Learning: Basic Understanding of working principles of neural networks and underlying algorithms (e.g., convolutional-CNN), recurrent-RNN-LSTM-GRU, back-propagation, loss function, gradient descent)

Data Wrangling and Lifecycle Maintenance: Experience in building and maintaining the pipeline of analytics models, using commonly used methodology (e.g., Airflow, MLflow)

Communication: Ability to articulate key messages concisely and precisely

Collaboration: Excellent interpersonal and teaming skills

Additional Preference
• Advanced Qualification: PhD in any Quantitative Discipline
• Eminence: Patents, publications, thought leadership, invited speakership and conspicuous presence in refereed platforms or forums of repute