Skills:-

• 5 – 7 years of experience in the data science field
• Experience Python, SQL and R. with building & deploy large scale machine learning models, e.g. random forest, xgboost, lightgbm, LSTM, Bert, etc..
• Experience in handling use cases that span classification, clustering, optimization, forecasting, etc.
• Experience in using cloud data platform solutions (ie. Google Big Query, Azure Synapse, Data Bricks, Snowflake etc..)
• Experience in defining, leading, delivering production grade ML Ops and post GO-Live success measurement of different data science projects.
• Experience in building and deploying machine-learning models in a production environment.
• Strong working knowledge of machine learning, data mining techniques and inference algorithms such as decision trees, association rules, clustering, classification, regression, topic models, stochastic sampling and collaborative filtering
• Strong data visualization skills using tools such as Tableau, Qlik, PowerBi
• Data manipulation and extraction skills
• Experience with Hadoop, Spark
• Knowledge of NLP techniques
• Experience of big data platforms
• Experience with ETL tools
• Strong working knowledge of Python & Computer Vision
• Solid knowledge of Python Machine learning libraries (Scikit Learn, Pandas, NumPy, SciPy, Matplotlib)

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With growing technologies like the Internet of Things (IoT), Machine Learning, Artificial Intelligence, etc., the need for structured data is essential in developing business ideas. To realize the development of structured and useable data, the field of Data Science employs data collection methods, analysis, and manipulation to find patterns in them. This makes data scientists an indispensable part of any organization dealing with data.

Data Scientist is a field of study that combines scientific methods, programming skills, domain expertise, and the knowledge of statistics and mathematics. Using these data, scientists extract meaningful insights from noisy or unstructured data and translate them into tangible business value.