Data Scientist

What we are looking for
As a Full stack Data Scientist, you will be responsible to build, optimize our AI/ML systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive capabilities.

Must: NLP (Should be able to build the models with use cases like Sentiment Analysis, Named Entity Recognition, Text Summarization, Information Retrieval, Topic Modeling, Text Classification, and Keyword Extraction),

Tech stack: PyTorch with the ability to use pre-trained models from huggingface or similar open-source models and repurpose them for our use cases.

At least two of these Skills along with NLP: Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision

Responsibilities

    Research and implement appropriate ML algorithms and tools
    Envision, implement, and deliver production-level NLP models
    Deploy ML models into production using cutting edge deployment strategies, conduct A/B tests to objectively measure improvements
    Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production
    Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning platform on Cloud (ML ops)
    Building Features, running tests, performing statistical analysis, and interpreting test results

Qualifications

    Masters or PhD with emphasis on Data Science, Machine learning, or Statistics
    2-5 years of Data Science Experience, 2+ years of experience for Masters, 1+ years for PhD
    Proficient in any of the deep learning frameworks such as PyTorch, TensorFlow or Keras
    Familiarity with Dockers and Kubernetes for deploying automation pipelines to production environments or Deploying Machine Learning models in AWS, GCP or Azure
    Experience in building, deploying, and improving Machine Learning models and algorithms in real-world products with expertise in NLP, NLU
    Excellent understanding of software engineering principles and design patterns
    Experience in one of the cloud platforms
    Ability to communicate the results of analysis
    Highly effective time management, communication, and organizational skills
    Having worked on problems related to NLP, Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision in solving problems within a large organization

What we are looking for
As a Full stack Data Scientist, you will be responsible to build, optimize our AI/ML systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive capabilities.

Must: NLP (Should be able to build the models with use cases like Sentiment Analysis, Named Entity Recognition, Text Summarization, Information Retrieval, Topic Modeling, Text Classification, and Keyword Extraction),

Tech stack: PyTorch with the ability to use pre-trained models from huggingface or similar open-source models and repurpose them for our use cases.

At least two of these Skills along with NLP: Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision

Responsibilities

    Research and implement appropriate ML algorithms and tools
    Envision, implement, and deliver production-level NLP models
    Deploy ML models into production using cutting edge deployment strategies, conduct A/B tests to objectively measure improvements
    Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production
    Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning platform on Cloud (ML ops)
    Building Features, running tests, performing statistical analysis, and interpreting test results

Qualifications

    Masters or PhD with emphasis on Data Science, Machine learning, or Statistics
    2-5 years of Data Science Experience, 2+ years of experience for Masters, 1+ years for PhD
    Proficient in any of the deep learning frameworks such as PyTorch, TensorFlow or Keras
    Familiarity with Dockers and Kubernetes for deploying automation pipelines to production environments or Deploying Machine Learning models in AWS, GCP or Azure
    Experience in building, deploying, and improving Machine Learning models and algorithms in real-world products with expertise in NLP, NLU
    Excellent understanding of software engineering principles and design patterns
    Experience in one of the cloud platforms
    Ability to communicate the results of analysis
    Highly effective time management, communication, and organizational skills
    Having worked on problems related to NLP, Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision in solving problems within a large organization

What we are looking for
As a Full stack Data Scientist, you will be responsible to build, optimize our AI/ML systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive capabilities.

Must: NLP (Should be able to build the models with use cases like Sentiment Analysis, Named Entity Recognition, Text Summarization, Information Retrieval, Topic Modeling, Text Classification, and Keyword Extraction),

Tech stack: PyTorch with the ability to use pre-trained models from huggingface or similar open-source models and repurpose them for our use cases.

At least two of these Skills along with NLP: Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision

Responsibilities

    Research and implement appropriate ML algorithms and tools
    Envision, implement, and deliver production-level NLP models
    Deploy ML models into production using cutting edge deployment strategies, conduct A/B tests to objectively measure improvements
    Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production
    Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning platform on Cloud (ML ops)
    Building Features, running tests, performing statistical analysis, and interpreting test results

Qualifications

    Masters or PhD with emphasis on Data Science, Machine learning, or Statistics
    2-5 years of Data Science Experience, 2+ years of experience for Masters, 1+ years for PhD
    Proficient in any of the deep learning frameworks such as PyTorch, TensorFlow or Keras
    Familiarity with Dockers and Kubernetes for deploying automation pipelines to production environments or Deploying Machine Learning models in AWS, GCP or Azure
    Experience in building, deploying, and improving Machine Learning models and algorithms in real-world products with expertise in NLP, NLU
    Excellent understanding of software engineering principles and design patterns
    Experience in one of the cloud platforms
    Ability to communicate the results of analysis
    Highly effective time management, communication, and organizational skills
    Having worked on problems related to NLP, Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision in solving problems within a large organization

What we are looking for
As a Full stack Data Scientist, you will be responsible to build, optimize our AI/ML systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive capabilities.

Must: NLP (Should be able to build the models with use cases like Sentiment Analysis, Named Entity Recognition, Text Summarization, Information Retrieval, Topic Modeling, Text Classification, and Keyword Extraction),

Tech stack: PyTorch with the ability to use pre-trained models from huggingface or similar open-source models and repurpose them for our use cases.

At least two of these Skills along with NLP: Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision

Responsibilities

    Research and implement appropriate ML algorithms and tools
    Envision, implement, and deliver production-level NLP models
    Deploy ML models into production using cutting edge deployment strategies, conduct A/B tests to objectively measure improvements
    Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production
    Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning platform on Cloud (ML ops)
    Building Features, running tests, performing statistical analysis, and interpreting test results

Qualifications

    Masters or PhD with emphasis on Data Science, Machine learning, or Statistics
    2-5 years of Data Science Experience, 2+ years of experience for Masters, 1+ years for PhD
    Proficient in any of the deep learning frameworks such as PyTorch, TensorFlow or Keras
    Familiarity with Dockers and Kubernetes for deploying automation pipelines to production environments or Deploying Machine Learning models in AWS, GCP or Azure
    Experience in building, deploying, and improving Machine Learning models and algorithms in real-world products with expertise in NLP, NLU
    Excellent understanding of software engineering principles and design patterns
    Experience in one of the cloud platforms
    Ability to communicate the results of analysis
    Highly effective time management, communication, and organizational skills
    Having worked on problems related to NLP, Tree-Based Methods, Time Series/Forecasting, Reinforcement Learning, and Computer Vision in solving problems within a large organization