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• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 6th Sep 2023

• Apply machine learning algorithms and statistical models to solve complex business problems and generate actionable insights.

• Design, develop, and implement data science solutions, including feature engineering, model development, and evaluation. 

• Architect scalable and efficient data pipelines for data preprocessing, feature extraction, and model training. 

• Conduct exploratory data analysis (EDA) to understand data characteristics, identify patterns, and gain insights into data quality and availability. 

• Mentor and lead junior data scientists, providing technical guidance and fostering their growth and development. 

• Communicate complex analytical concepts and findings to both technical and non-technical stakeholders in a clear and concise manner. 

• Stay updated with the latest advancements in machine learning algorithms, tools, and techniques. 

Must Have:
• Bachelors or Masters degree in a quantitative field such as Mathematics, Statistics, Computer Science, or related disciplines. 

• Minimum of 3 years of experience as a Data Scientist, with a focus on machine learning and exploratory data analysis. 

• Proficiency in machine learning algorithms, statistical models, and their practical application. 

• Strong programming skills in Python, with Pandas/NumPy experience, for data manipulation, model development, and evaluation.

• Solid understanding of data preprocessing techniques, feature engineering, and model evaluation methods. 

• Experience in designing and implementing scalable data pipelines for preprocessing, feature extraction, and model training.

• Strong problem-solving and analytical skills, with the ability to think critically and creatively. 

• Excellent communication and leadership skills, with the ability to mentor and lead junior data scientists. 

• Experience with end-to-end problem solving and ownership for at least one major thread of a data science project 

• Familiarity with the technological stack needed to deliver data science projects end to end - Git or any other VCS, orchestration tools etc. 

Nice to Have:
• Experience with ML on cloud-based data platforms and services, such as AWS, Azure, or Google Cloud Platform 

• Experience with deep learning frameworks such as TensorFlow or PyTorch. 

• Familiarity with big data technologies such as Hadoop, Spark, or distributed computing frameworks. 

• Knowledge of natural language processing (NLP) techniques and tools. 

• Proficiency in data visualization tools, such as Plotly or Matplotlib, for presenting insights and results. 

• Active participation in data science communities, conferences, or open-source projects. 

• Publications or patents in the field of data science or machine learning