Senior Associate Data Scientist (Telangana)

Job Responsibilities: - Develop and deploy machine learning models and generative AI capabilities. - Design, code, test, and debug applications. - Collaborate with cross-functional teams to achieve common goals. - Keep stakeholders informed on development progress and benefits. - Manage project lifecycle and software development deliverables. - Develop and implement machine learning models and algorithms to optimize AI operations and enhance system performance. - Collaborate with cross-functional teams to identify business needs and translate them into data-driven solutions. - Analyze large datasets to extract actionable insights and support strategic decision-making. - Design and conduct experiments to validate model performance and improve operational processes. - Monitor and maintain AI models in production, ensuring they operate effectively and efficiently. - Mentor junior data scientists and contribute to the development of best practices in data science and AI Ops - Solve complex problems and handle ambiguity with robust analytical skills. - Develop insights, methods, or tools using various analytic methods such as causal-model approaches, predictive modeling, regressions, machine learning, time series analysis, etc. - Handle large amounts of data from multiple and disparate sources, employing advanced Python and SQL techniques to ensure efficiency and accuracy. - Uphold the highest standards of data integrity and security, aligning with both internal and external regulatory requirements and compliance protocols. Required qualifications, capabilities, and skills : - Bachelors or Masters Degree in Finance, Quantitative Finance, Data Science, Economics, or a related field. - Proficient programming skills in python and knowledge of software engineering best practices - Strong knowledge of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark) - Understanding of the main deep-learning frameworks such as PyTorch, TensorFlow, Keras - Experience with Linux and shell scripting and experience with LaTeX - Solid understanding of traditional data science techniques and experience with data engineer pipelines for big data - Solid knowledge of RNNs, and LSTMs models. .