Data Scientist - ML, Python

Data Scientist - ML, Python Design, develop, and deploy scalable applications using Python, with a strong focus on machine learning solutions. Build and optimize data processing pipelines using Spark, Pandas, NumPy, and Scikit-learn. Design autonomous AI workflows, build multi-step reasoning agents. Build integrations between AI models and enterprise systems, expose tools/data through MCP servers; manage context sharing. Develop and maintain mission-critical, highly available enterprise applications. Design, train, and evaluate supervised and unsupervised machine learning models, ensuring model accuracy and performance. Apply advanced knowledge of machine learning algorithms (e.g., One-Class SVM, K-Means, clustering, anomaly detection techniques). Leverage a strong foundation in mathematics, statistics, and statistical modeling (R knowledge is a plus). Work extensively in Linux environments, managing systems in high-traffic, production-grade setups. Develop and integrate REST APIs, web services, and API integrations. Collaborate effectively within cross-functional teams, demonstrating strong communication and stakeholder engagement skills. Key Responsibilities: Develop machine learning algorithms using Python and Tensorflow to merge, manage, and extract data, delivering tailored reports to stakeholders. Apply statistical techniques and machine learning frameworks such as Pytorch to design custom data models and algorithms, enhancing data processing capabilities. Utilize SQL to query large datasets, identifying meaningful insights and interpreting findings through data mining and exploratory data analysis. Collaborate with business stakeholders to identify and prioritize opportunities for data-driven solutions that support organizational goals. Generate comprehensive reports and visualizations that translate complex data analysis into actionable insights for stakeholders, informing business decisions. Skill Requirements: Strong understanding of machine learning concepts and frameworks, including Tensorflow and Pytorch. Proficient in Python programming for data manipulation and algorithm development. In-depth knowledge of SQL for effective data querying and management. Familiarity with statistical methods and data mining techniques for analyzing large datasets. Excellent communication skills to convey technical findings to non-technical stakeholders. Other Requirements: Optional certifications: Certified Data Scientist, Tensorflow Developer Certificate, or relevant machine learning certifications are valuable. Information at a Glance HCLTech