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Main Responsibilities:

1. Perform advanced data analysis and develop sophisticated predictive and prescriptive models:
2. This includes using statistical and machine learning techniques to extract insights from data and develop models that can be used to predict future outcomes or prescribe actions.
3. Explore and preprocess data to ensure data quality and suitability for analysis: This includes cleaning, formatting, and transforming data to make it ready for analysis.
4. Design and conduct experiments and A/B tests to validate hypotheses and assess model performance: This includes designing experiments to test the effectiveness of different approaches to data analysis and machine learning.
5. Develop and deploy machine learning models into production environments: This includes making sure that machine learning models are working properly and that they can be used to make predictions or recommendations in real time.
6. Collaborate with other teams to apply data science to solve complex business problems: This includes working with stakeholders to understand their needs, and developing data-driven solutions that can help them achieve their goals.
7. Deliver measurable business value through data-driven insights and recommendations: This includes using data science to identify opportunities to improve the business, and developing and implementing solutions that can help the business achieve its goals.
8. Conducting data analysis
9. Developing data visualizations
10.  Integrating data with other applications
11. Troubleshooting data problems
12. Stay abreast of the latest data science advancements and industry trends
13. Writing data documentation Qualification

Experience, and Skills:

• Bachelor's degree in computer science, statistics, mathematics or a related field (preferred)
• Minimum 0-3 years of experience in the relevant field.
• Proven experience in ETL/ELT, Oracle Data Integrator (ODI) is preferred.
• Strong analytical thinking and problem-solving capabilities
• Effective communication and interpersonal skills
• Strong SQL queries, data modeling concepts are mandatory.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience working with ML/DL frameworks like Scikit-Learn, TensorFlow, Keras, PyTorch, etc
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, proper usage, etc.) and experience with applications.
• Expert knowledge and Experience in working on conventional Computational Linguistics problems such as Syntactic Processing, Word Sense Disambiguation, Context-Free grammar, Lexical Semantics, Quantification, Plurality, etc.
• Experience using statistical computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets.

Skills:

Interpersonal Skills, Communication Skills, Advanced Statistical Techniques, Data Modelling,