Key Responsibilities:
As the successful candidate you will be required to perform the following:
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company data sources to drive optimization and improvement of product development, and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop custom data models and algorithms to apply to datasets.
Support ideation endeavors in packaging new ideas/products and preparing them for minimal viable product development.
Assess AI applicability in enhancing current business processes.
Minimum Requirements:
As the successful candidate you must hold a Master of Science or PhD degree in data science, computer science, computer vision, applied mathematics or a related field.
You must have a minimum of 8 years of hands-on experience in Data Science & AI projects (Generative AI, Computer Vision, Natural Language Processing (NLP), Time Series). Experience in the energy sector is a plus.
You must be able to demonstrate experience of bringing ideas from conceptualization to productionalization using the right tools (e.g. mlflow, kubeflow, tensorlight, etc).
You must also be able to showcase a very strong expertise in data collection, cleaning, and preprocessing, and wrangling.
You should be fluent in either R, or Python; both is preferred, and familiarity with golang is a plus.
You must have strong experience using a variety of machine learning techniques, methods, and can rationally and scientifically decide when to use what.
You should have at least 5 years of experience in building computer vision-based product.
You should be able to apply transfer learning on models like, Yolo, ViT, ResNet, Unet, AlexNet, etc.
You must be able to build object detection models, face/gesture recognition, and identification engines.
You must have the ability to design, develop and deploy systems based on GenAI technology.
You must be proficient in deep learning tools keras, tensorflow and pytorch.
You must have deep knowledge and understanding of Large Language and Vision Model Transformer Architectures.
You must have the ability to design, develop and deploy systems based on GenAI technology.
You should be experienced in Information Retrieval (Content Recommendation, Search Metrics, Search Query, document classification, entity recognition, topic modelling, etc).
You should be proficient in transfer learning and in fine tuning open-sourced transformers models such as LAMA, Mistral, Gemma, LLAVA, QWen and Intern.
You should have least 5 years of experience in building time series forecasting models.
You should be expert in time series forecasting models and in using technologies like LSTMs, Prophet, and time series analysis.
You should be proficient in using sklearn pandas, numpy, plotly, seaborn, and relevant R libraries if R is their preferred language.
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