What Jobs are available for Senior Scientist Nlp Machine Learning Data Mining Professional in India?

• Master's or PhD in Computer Science, Statistics, Data Science, or a related quantitative field.
• Minimum of 5 years of hands-on experience in data science and machine learning.
• Proficiency in programming languages such as Python or R, and experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Strong understanding of statistical modeling, data mining, and machine learning algorithms.
• Experience with big data technologies (e.g., Spark, Hadoop) and databases (SQL, NoSQL).
• Excellent data visualization and communication skills.
• Experience working with cloud platforms (AWS, Azure, GCP) is a plus.
• Ability to work effectively in a hybrid environment, collaborating with colleagues both in-office and remotely.

• Collect, clean, and preprocess large and complex datasets from various sources.
• Perform exploratory data analysis to identify trends, patterns, and insights.
• Develop, train, and evaluate machine learning models for tasks such as classification, regression, clustering, and recommendation systems.
• Implement and optimize algorithms for predictive modeling and forecasting.
• Deploy machine learning models into production environments and monitor their performance.
• Collaborate with business stakeholders to understand their needs and translate them into data science solutions.
• Design and conduct A/B tests and other experiments to validate hypotheses.
• Stay current with the latest research and advancements in machine learning and artificial intelligence.
• Communicate complex findings and recommendations clearly through visualizations and presentations.
• Contribute to the development of data infrastructure and tooling.
• Mentor junior data analysts and scientists.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Proven experience as a Data Scientist with a strong portfolio of machine learning projects.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).
• Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with SQL and database management.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Ability to work effectively in a collaborative team environment.

Company Overview

Cloudious LLC, headquartered in San Jose, California, is a pioneering force in the Information Technology & Services industry. We specialize in connecting companies with top-tier talent across sectors like technology, healthcare, and finance. With a team of 201-500 employees, we strive to solve our clients' staffing challenges efficiently. Our expertise spans decades, dedicated to fostering trusted partnerships with leading organizations globally.

Job Overview

We are seeking a Senior Machine Learning Data Scientist for a contract, full-time position in Bangalore. The candidate should have up to 10 years of work experience. As a key member of our team, you will leverage advanced machine learning techniques to drive impactful solutions, drawing from a robust understanding of data science, natural language processing, and large language models. This role is critical for influencing decisions and innovating within varied industry domains.

Qualifications and Skills

• Proficiency in data science with the ability to formulate, implement, and validate advanced machine learning strategies and techniques.
• Extensive experience in natural language processing (Mandatory skill) for developing algorithms that enhance textual data understanding.
• Deep understanding of large language models (LLM) and their applications (Mandatory skill) to solve industry-specific challenges.
• Strong command of machine learning concepts and practices, including both traditional and modern approaches.
• Expertise in Python programming for efficient data manipulation and analysis to build robust models and scalable solutions.
• Experience with PyTorch framework to design and implement deep learning models effectively in production environments.
• Strong problem-solving skills with a focus on delivering data-driven insights and actionable recommendations to stakeholders.
• Ability to work collaboratively in a team setting and communicate complex technical concepts to non-technical stakeholders clearly.

Roles and Responsibilities

• Develop and deploy machine learning models to solve a wide array of complex problems that meet industry demands.
• Lead efforts in the application of natural language processing and large language models to improve data interpretation and insights.
• Collaborate with cross-functional teams to integrate machine learning solutions into business processes and strategies.
• Mentor junior data scientists and contribute to the growth of the teams technical expertise.
• Analyze and process large datasets, ensuring quality and integrity to derive meaningful insights and support decision-making.
• Stay abreast of emerging trends in machine learning and data science to implement cutting-edge developments in company projects.
• Communicate findings effectively with clear visualizations and reports to stakeholders at various levels.
• Ensure compliance with data protection regulations and company policies while conducting data operations.

• Conduct pioneering research in Machine Learning, Deep Learning, and Natural Language Processing to develop state-of-the-art AI models.
• Design, implement, and evaluate novel algorithms and architectures for tasks such as text generation, sentiment analysis, machine translation, question answering, and information extraction.
• Develop and deploy production-ready AI models, ensuring scalability, efficiency, and robustness.
• Collaborate with engineering teams to integrate AI models into existing products and services.
• Stay abreast of the latest advancements in AI research and identify opportunities for applying new techniques.
• Publish research findings in top-tier AI conferences and journals.
• Mentor junior researchers and engineers, providing technical guidance and fostering a culture of innovation.
• Analyze and interpret complex datasets to train and fine-tune AI models.
• Contribute to the development of the company's AI strategy and roadmap.
• Evaluate and select appropriate tools, frameworks, and platforms for AI development and deployment.
• Work on challenging problems in areas like explainable AI (XAI), ethical AI, and reinforcement learning.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• A minimum of 6 years of hands-on experience in AI research and development, with a strong publication record.
• In-depth knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers).
• Expertise in Natural Language Processing techniques and libraries (e.g., NLTK, spaCy, Hugging Face Transformers).
• Proficiency in programming languages such as Python, and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong mathematical and statistical foundation.
• Excellent problem-solving, analytical, and critical thinking skills.
• Proven ability to work independently and lead research projects.
• Strong communication and collaboration skills, with the ability to present complex technical concepts clearly.
• Experience with large-scale data processing and distributed computing is a plus.
• Familiarity with cloud platforms (AWS, GCP, Azure) for ML deployment is advantageous.

• Develop, train, and deploy machine learning models.
• Perform data cleaning, feature engineering, and exploratory data analysis.
• Select appropriate algorithms and tools for specific problems.
• Evaluate model performance and iterate for improvement.
• Collaborate with cross-functional teams to define project requirements.
• Identify new opportunities to apply AI/ML techniques.
• Communicate complex findings and recommendations to stakeholders.
• Stay updated with the latest research and trends in machine learning.
• Mentor junior data scientists and engineers.
• Ensure data privacy and security best practices.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience in data science and machine learning.
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop).
• Strong understanding of statistical modeling and data mining techniques.
• Excellent problem-solving and analytical skills.
• Strong communication and presentation abilities.

• Develop and deploy advanced machine learning models.
• Clean, process, and analyze large datasets to extract insights.
• Perform feature engineering and selection for model optimization.
• Build, train, and evaluate predictive and prescriptive models.
• Collaborate with engineering teams to integrate models into production systems.
• Conduct A/B testing and experiments to validate model performance.
• Stay current with the latest advancements in machine learning and AI.
• Communicate complex findings to stakeholders through visualizations and reports.
• Mentor junior data scientists and contribute to team knowledge sharing.
• Identify opportunities to leverage data science for business improvement.

• Master's/Ph.D. in Computer Science, Statistics, or related field.
• 5+ years of experience in data science and machine learning.
• Proficiency in Python or R, and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with SQL, Pandas, and data manipulation.
• Experience deploying ML models into production.
• Familiarity with big data technologies (Spark, Hadoop) is a plus.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent communication and data visualization abilities.
• Ability to work independently and collaboratively in a remote team.

• Lead the design, development, and implementation of sophisticated machine learning models and algorithms.
• Oversee data collection, cleaning, and feature engineering processes to ensure data quality and relevance.
• Conduct rigorous statistical analysis and hypothesis testing to validate model performance and derive actionable insights.
• Collaborate with cross-functional teams, including researchers, engineers, and domain experts, to define project scope and objectives.
• Mentor and guide junior data scientists, fostering a culture of learning and continuous improvement.
• Stay updated with the latest research and advancements in machine learning, deep learning, and artificial intelligence.
• Present complex findings and recommendations to both technical and non-technical stakeholders.
• Develop and maintain robust documentation for all developed models and processes.
• Ensure the ethical and responsible application of AI and machine learning techniques.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• 7+ years of experience in data science, with a significant focus on machine learning and predictive modeling.
• Proven experience leading data science projects and mentoring team members.
• Expertise in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn.
• Strong understanding of various machine learning algorithms (e.g., regression, classification, clustering, deep learning).
• Experience working with large, complex datasets and distributed computing frameworks (e.g., Spark).
• Excellent analytical, statistical, and problem-solving skills.
• Outstanding communication and presentation abilities.
• Demonstrated ability to work effectively in a remote, collaborative environment.

• Design, develop, and implement advanced machine learning models and algorithms for predictive analytics, pattern recognition, and decision support.
• Extract, clean, and transform large, complex datasets from various sources.
• Collaborate with research teams to understand their needs and translate them into data science solutions.
• Evaluate and select appropriate ML algorithms and techniques for specific problems.
• Deploy ML models into production environments and monitor their performance.
• Develop and maintain data pipelines and feature stores.
• Communicate complex findings and insights to both technical and non-technical stakeholders through compelling visualizations and reports.
• Stay up-to-date with the latest advancements in machine learning, AI, and data science.
• Mentor junior data scientists and contribute to the growth of the data science team.
• Contribute to the development of data strategy and roadmap.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5-9 years of professional experience in data science and machine learning, with a focus on model development and deployment.
• Strong proficiency in programming languages such as Python or R, and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Expertise in various machine learning techniques, including supervised and unsupervised learning, deep learning, and natural language processing.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills.
• Ability to work effectively in a hybrid work environment and collaborate with cross-functional teams.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Experience in the R&D sector is a plus.