Verified Job
IT / Software / Data Analyst
Newgen Software Technologies - Data Scientist - AI/ML Solutions
IT / Software / Data Analyst
#28136
Remote / WFH
Newgen Software Technologies Ltd.
Job Description
Position Overview :
We are looking for a passionate Data Scientist to develop end-to-end AI/ML solutions across machine learning, NLP, deep learning, and generative AI.
The role involves working on diverse datasets, building innovative models, and driving actionable insights for real-world business problems.
Key Responsibilities :
- Develop and deploy end-to-end data science solutions using ML, NLP, deep learning and generative AI techniques to meet business requirements.
- Design and experiment with novel model architectures, algorithms, and optimization strategies for improved performance.
- Analyze structured and unstructured data using statistical and machine learning methods to uncover trends, generate insights, and deliver actionable recommendations.
- Collaborate cross-functionally with product, engineering, and business teams to translate insights into scalable solutions.
- Present findings and models in a clear and compelling manner to technical and nontechnical stakeholders.
Required Skill Set :
- Strong foundation in statistics, data science methodologies, and hands-on experience with machine learning algorithms (KNN, SVM, Na- ve Bayes, Decision Trees, Neural Networks, Linear Regression).
- Proficient in Python (mandatory) with experience using libraries such as NumPy, pandas, SciPy.
- Basic familiarity with Java is an added advantage.
Preferred / Good to Have :
- Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Experience with large-scale data manipulation using PySpark, pandas, or NumPy.
- Exposure to real-world NLP applications including document classification, text analytics, and document data extraction.
- Working knowledge of computer vision concepts like object detection, image segmentation, and OpenCV.
- Understanding of advanced deep learning architectures : CNNs, RNNs, LSTM, and Transformer models.
- Prior experience handling large datasets and implementing scalable solutions using Spark
We are looking for a passionate Data Scientist to develop end-to-end AI/ML solutions across machine learning, NLP, deep learning, and generative AI.
The role involves working on diverse datasets, building innovative models, and driving actionable insights for real-world business problems.
Key Responsibilities :
- Develop and deploy end-to-end data science solutions using ML, NLP, deep learning and generative AI techniques to meet business requirements.
- Design and experiment with novel model architectures, algorithms, and optimization strategies for improved performance.
- Analyze structured and unstructured data using statistical and machine learning methods to uncover trends, generate insights, and deliver actionable recommendations.
- Collaborate cross-functionally with product, engineering, and business teams to translate insights into scalable solutions.
- Present findings and models in a clear and compelling manner to technical and nontechnical stakeholders.
Required Skill Set :
- Strong foundation in statistics, data science methodologies, and hands-on experience with machine learning algorithms (KNN, SVM, Na- ve Bayes, Decision Trees, Neural Networks, Linear Regression).
- Proficient in Python (mandatory) with experience using libraries such as NumPy, pandas, SciPy.
- Basic familiarity with Java is an added advantage.
Preferred / Good to Have :
- Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Experience with large-scale data manipulation using PySpark, pandas, or NumPy.
- Exposure to real-world NLP applications including document classification, text analytics, and document data extraction.
- Working knowledge of computer vision concepts like object detection, image segmentation, and OpenCV.
- Understanding of advanced deep learning architectures : CNNs, RNNs, LSTM, and Transformer models.
- Prior experience handling large datasets and implementing scalable solutions using Spark
