Data Science Engineer

Job Description

AI Cyber Solutions is looking for an enthusiastic data science engineer to take and-to-end responsibility for processing systems and large-scale databases. The candidate would be involved in developing and designing architectures and AI or ML services. Besides, you’d also test and maintain the databases and systems. As a part of your role, you may have to clean and wrangle raw data to keep it readily available for analysis.

Skills Required

  • Python, Linux OS, Pandas, Scikit-learn, and other machine learning libraries
  • Experience in deep learning on NLP/NLU is a big plus
  • Solid understanding of mathematical underpinnings behind Machine Learning algorithms such as Probability, Statistics, Linear Algebra. 
  • Strong Understanding of ML concepts – Probabilistic Models, Supervised and Unsupervised Learning, Neural Networks, Support Vector Machines
  • Has hands-on knowledge on setting up Docker containerization and running application on ECS,EKS
  • Very good exposure in setting up Analytical tools such as RStudio, MLFLOW, Databricks, Jupyter etc.
  • Bachelors/Masters in Computer Science, Engineering, Statistic/Mathematics or relevant field; graduate degree in Data Science or another quantitative field is preferred

Tasks to be Performed

Work with deep data and analytics skills with strong business acumen to solve business problems by understanding, preparing, and analyzing data to predict emerging trends and provide recommendations to optimize business results.


Experience using statistical computer languages R, Python, SLQ, NoSQL databases etc. to manipulate data and draw insights from large data sets


Build topic analysis, text classification, named entity recognition methods for unstructured and semi-structured data


Experience with Python ML libraries; Apache Spark and Kafka.


Proficiency in machine learning techniques and data mining algorithms such as Regression, Clustering, Classification, Decision trees, KNN and SVM


Ability to design algorithmic implementation for performing real-time and scalable learning machines


Knowledge of open source machine learning libraries like scikit-learn, TensorFlow, NLP tool as NLTK


Demonstrate and Document working prototype on test datasets and real-world scenarios.

Demonstrate and Document working prototypes on test datasets and real-world scenarios.


You’ll utilize the latest techniques in AI, ML (including Deep Learning approaches) and NLU


Build topic analysis, text classification, named entity recognition methods for unstructured and semi-structured data


Develop and perform text classification using methods such as logistic regression, decision trees, SVM and maximum entropy classifiers


Perform text mining, generate and test working hypotheses, prepare and analyze historical data and identify patterns


Generate creative solutions (patents) and publish research results in top conferences (papers)


Design and develop AI/ML services on the platform


Design and Develop customer use cases and applications


Innovate to come up with new solutions and improve existing solutions.


Be an enthusiastic and motivated member of the team.