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51 jobs found for Scientist In India

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  • 1. Invent and design new technology and find new uses for existing technology. 2. Formulate technology strategy and architecture as per business requirement. 3. Help engineers solve complex computing problems. 4. Define architecture and best practices for Blockchain technology adoption and implementation. 5. Disseminate best practices and act as a knowledgeable resource for Blockchain engineering problem ...

  • 1. Invent and design new technology and find new uses for existing technology. 2. Formulate technology strategy and architecture as per business requirement. 3. Help engineers solve complex computing problems. 4. Define architecture and best practices for Blockchain technology adoption and implementation. 5. Disseminate best practices and act as a knowledgeable resource for Blockchain engineering problem ...

  • Solid understanding of statistical analysis, machine learning and data-modeling. Experience in predictive modeling and analysis. Practical experience with machine learning tool kits and frameworks At least 2-5 years of working experience using Java, Python, R in doing data engineering and data modeling Possess at least a Degree or Diploma in computer science / IT related; Willingness to learn and able to ...

  • EXP:3-8 Yrs Skills : Machine learning,Python,Predictive modeling,SAS,R,Big data Excellent Communication

  • Exp : 4-8 years work location:Bangalore and Chennai We are looking for strong hands-on person with knowledge in Deep Learning and Machine Learning using python. We can give up on Deep learning if the person comes from a solid ML background and it is not possible if the person has not done enough or if the person is not coming from a solid background. People who are good, would probably have worked on ...

  • Exp : 4-8 years work location:Bangalore and Chennai We are looking for strong hands-on person with knowledge in Deep Learning and Machine Learning using python. We can give up on Deep learning if the person comes from a solid ML background and it is not possible if the person has not done enough or if the person is not coming from a solid background. People who are good, would probably have worked on ...

  • Experience- 2 to 8 Years of Experience Skills Required- Machine Learning, NLP and Artificial Intelligence with R/SAS/Python. Experience in Building Models is a must and not into reporting

  • learning libraries such as SparkML, Shogun, Mahout and OpenNLP. The Data Scientist will be responsible for developing advanced predictive /prescriptive systems, creating efficient algorithms for business problem solving, improving data quality Experience with industry scale data mining and/or text mining

  • learning libraries such as SparkML, Shogun, Mahout and OpenNLP. The Data Scientist will be responsible for developing advanced predictive /prescriptive systems, creating efficient algorithms for business problem solving, improving data quality Experience with industry scale data mining and/or text mining

  • learning libraries such as SparkML, Shogun, Mahout and OpenNLP. The Data Scientist will be responsible for developing advanced predictive /prescriptive systems, creating efficient algorithms for business problem solving, improving data quality Experience with industry scale data mining and/or text mining

  • will be involved in complex projects, sometimes across several business units and functions. You will work under the guidance of a senior data scientist and will be responsible for delivering solutions to business problems. This role requires a strong level of data science knowledge as well as experience with data

  • will be involved in complex projects, sometimes across several business units and functions. You will work under the guidance of a senior data scientist and will be responsible for delivering solutions to business problems. This role requires a strong level of data science knowledge as well as experience with data

  • Strong working knowledge in Python. Strong at collecting, cleansing and reshaping unstructured/raw datasets. Strong understanding of ML concepts - Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks & Deep learning, Ensembling. Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. Exposure to Optimization ...

  • Strong working knowledge in Python. Strong at collecting, cleansing and reshaping unstructured/raw datasets. Strong understanding of ML concepts - Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks & Deep learning, Ensembling. Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. Exposure to Optimization ...

  • Strong working knowledge in Python. Strong at collecting, cleansing and reshaping unstructured/raw datasets. Strong understanding of ML concepts - Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks & Deep learning, Ensembling. Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. Exposure to Optimization ...

  • Strong working knowledge in Python. Strong at collecting, cleansing and reshaping unstructured/raw datasets. Strong understanding of ML concepts - Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks & Deep learning, Ensembling. Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. Exposure to Optimization ...

  • Strong working knowledge in Python. Strong at collecting, cleansing and reshaping unstructured/raw datasets. Strong understanding of ML concepts - Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks & Deep learning, Ensembling. Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. Exposure to Optimization ...

  • Strong working knowledge in Python. Strong at collecting, cleansing and reshaping unstructured/raw datasets. Strong understanding of ML concepts - Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks & Deep learning, Ensembling. Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. Exposure to Optimization ...

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