Responsibilities:

• Select appropriate datasets and data representation methods

• Data mining using state-of-the-art techniques

• Assess the effectiveness and accuracy of new data sources and data gathering techniques

• Create and maintain optimal data pipeline architecture

• Assemble large, complex data sets that meet functional / non-functional business requirements

• Design and developing machine learning systems

• Perform statistical analysis and fine-tuning the models

• Coordinate with different functional teams to implement models and monitor outcomes

• Implement appropriate ML algorithms to develop and deploy AI models into production and maintain the quality and accuracy of the Model solutions during the deployments

• Extend existing ML libraries and frameworks
  
  
  
  Skills And Experience :
  
  
  
  
  • Proficient in R, Python, SQL and data visualization tools like Tableau
  
  
  
  


• 
  
  
  
  • Minimum 3 years of experience as a Machine learning Engineer
  
  
  • Experience in deploying ML projects in production environment
  
  
  
  


• Excellent communication and presentation skills


• Strong math skills (e.g. statistics, algebra)

• Good applied statistics skills, such as distributions, statistical testing, regression, etc.

• Experience in extensive data pre-processing and transformation

• Knowledge of Linear algebra, Probability theory, Statistics, Hypothesis Testing and Optimization techniques

• Working knowledge on the techniques like Descriptive and Inferential Statistics and performing basic predictive modelling

• Working knowledge of various ML models and techniques like Statistics, Linear regression, Logistic regression, Decision tree, Random forest, XGBoost, Neural Networks, etc.

• Good understanding of ML tools/libraries like Tensorflow, Keras, Pandas, Spacy, Pytorch, NLTK, SkLearn etc.

• Hands on experience with Big Data technology stack like: Spark, HDFS, Hadoop, Hive, Pig is an added advantage