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Data Scientist - SQL/Python


Idyllic Services Pvt Ltd


Location

Pune | India


Job description

Job Description :Must to have skills : Python, Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. - Advanced SQL skills with SQL Server and Spark - Excellent programming skills in Python. - Strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. - Advanced SQL skills with SQL Server and Spark experience. - Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Network.- Experience with cloud platforms such as Azure, AWS is preferred but not require - Experience of big data program preferable - Enthusiastic and energetic problem solver to join an ambitious team. - Business analysis skills, defining and understanding requirements - Attention to detail. - Ability to communicate effectively in a multi-program environment across a range of stakeholdersResponsibilities : Data Exploration and Analysis : - Analyze large datasets to extract meaningful insights, identify trends, and uncover patterns using statistical and machine learning techniques. Predictive Modeling : - Develop and implement predictive models to forecast trends, outcomes, and behavior based on historical data. Machine Learning Algorithms : - Design, build, and deploy machine learning models for various business applications, optimizing for accuracy and efficiency. Data Cleaning and Preprocessing : - Clean and preprocess raw data to ensure quality and reliability. - Handle missing data and outliers effectively. Feature Engineering : - Identify and create relevant features that enhance the performance of machine learning models. Data Visualization : - Communicate findings effectively through data visualization tools and techniques. - Create dashboards and reports to present insights to stakeholders. Collaboration with Cross-Functional Teams : - Work closely with business analysts, engineers, and other departments to support ongoing projects and ensure seamless integration of machine learning models. Experimentation and A/B Testing : - Conduct experiments and A/B testing to validate hypotheses and improve model performance. Model Deployment : - Collaborate with IT teams to deploy and integrate models into production systems. Continuous Learning : - Stay abreast of the latest developments in data science, machine learning, and related fields. - Implement new techniques and methodologies to enhance the data science capabilities of the team. (ref:hirist.tech)


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