What Data Science Jobs are in Jaipur?

• Design, implement, and optimize deep learning models for various applications (e.g., computer vision, NLP, reinforcement learning).
• Develop and maintain robust machine learning pipelines for data preprocessing, training, evaluation, and deployment.
• Collaborate with data scientists and researchers to translate research concepts into scalable ML solutions.
• Monitor and improve the performance, scalability, and reliability of deployed ML models.
• Stay up-to-date with the latest advancements in deep learning research and industry trends.
• Experiment with new architectures, algorithms, and tools to enhance model capabilities.
• Write clean, efficient, and well-documented code in Python or other relevant languages.
• Troubleshoot and resolve issues related to model performance and infrastructure.
• Contribute to the team's knowledge sharing and best practices in ML engineering.
• Ensure adherence to coding standards and deployment best practices.

• Master's or Ph.D. in Computer Science, Electrical Engineering, Artificial Intelligence, or a related quantitative field.
• 3+ years of hands-on experience in machine learning engineering with a strong focus on deep learning.
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong understanding of various deep learning architectures (CNNs, RNNs, Transformers, GANs).
• Experience with data manipulation, feature engineering, and model evaluation techniques.
• Familiarity with cloud platforms (AWS, Azure, GCP) and ML services.
• Experience with containerization technologies (Docker) is a plus.
• Excellent problem-solving, analytical, and debugging skills.
• Strong communication and teamwork abilities.
• Ability to work effectively in a fast-paced, research-oriented environment.

Our client, a globally recognized leader in artificial intelligence research and development, is seeking a highly skilled and innovative Senior AI/ML Research Scientist specializing in Natural Language Processing (NLP) . This fully remote position offers the exciting opportunity to push the boundaries of AI by developing novel NLP models and techniques. You will work on challenging problems related to text understanding, generation, machine translation, and dialogue systems, contributing to state-of-the-art AI applications. The ideal candidate possesses a strong theoretical foundation in NLP and deep learning, coupled with practical experience in implementing and evaluating complex models. Join a team of world-class researchers dedicated to advancing AI, working from anywhere in a flexible, remote capacity.

• Conduct cutting-edge research in Natural Language Processing, including areas like language modeling, sentiment analysis, information extraction, and question answering.
• Develop, implement, and evaluate novel NLP algorithms and deep learning architectures (e.g., Transformers, LSTMs).
• Process and analyze large-scale text datasets to train and fine-tune models.
• Collaborate with other researchers and engineers to integrate NLP models into various AI applications and products.
• Publish research findings in top-tier AI/NLP conferences and journals.
• Stay abreast of the latest advancements in NLP, machine learning, and related fields.
• Mentor junior researchers and contribute to the team's knowledge base and best practices.
• Design and execute experiments to rigorously test hypotheses and model performance.
• Contribute to the strategic direction of NLP research within the organization.

• Ph.D. in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field with a specialization in NLP.
• Minimum of 6 years of post-doctoral research experience in NLP and deep learning.
• Proven expertise in developing and applying advanced NLP techniques and models.
• Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Proficiency in NLP libraries like Hugging Face Transformers, NLTK, SpaCy.
• Solid understanding of statistical methods, machine learning algorithms, and deep learning architectures.
• Demonstrated ability to publish research in leading AI/NLP venues (e.g., ACL, EMNLP, NeurIPS).
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills, essential for a remote team environment.
• Experience with large-scale data processing and cloud computing platforms is a plus.

Our client offers a highly competitive salary, comprehensive benefits, and a generous bonus structure. As a fully remote position, you'll enjoy unparalleled flexibility in your work location. We provide extensive opportunities for professional development, conference attendance, and collaboration with leading AI researchers worldwide. Join our innovative and globally distributed team in Jaipur and contribute to groundbreaking advancements in artificial intelligence and NLP.

• Develop, implement, and deploy advanced statistical models and machine learning algorithms.
• Analyze large, complex datasets to identify trends, patterns, and insights relevant to financial services.
• Build predictive models for areas such as customer churn, credit scoring, fraud detection, and market forecasting.
• Design and execute A/B tests and other experiments to validate hypotheses and measure impact.
• Collaborate with product managers, engineers, and business stakeholders to define data requirements and translate business problems into analytical solutions.
• Communicate complex findings and recommendations clearly and effectively to both technical and non-technical audiences.
• Mentor junior data scientists and contribute to the overall growth of the data science practice.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Ensure the quality, integrity, and governance of data used for analysis and modeling.
• Contribute to the development of data infrastructure and tooling.

• Master's or PhD in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
• Minimum of 5 years of hands-on experience as a Data Scientist, with a significant focus on financial services.
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining techniques.
• Proficiency in programming languages commonly used in data science, such as Python or R, and their associated libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
• Experience with SQL and working knowledge of big data technologies (e.g., Spark, Hadoop).
• Strong understanding of financial markets, products, and common business challenges in the Banking & Finance sector.
• Excellent analytical, problem-solving, and critical thinking skills.
• Proven ability to communicate complex technical concepts to diverse audiences.
• Experience working in a remote, collaborative team environment.
• Prior experience with data visualization tools is a plus.

• Develop and implement advanced statistical and machine learning models to address key business challenges in areas like customer segmentation, recommendation systems, and fraud detection.
• Clean, transform, and analyze large, complex datasets to identify trends, patterns, and insights.
• Design and execute A/B tests and other experiments to evaluate the impact of new features and strategies.
• Collaborate with engineering, product, and marketing teams to integrate data-driven insights and models into product development and business operations.
• Communicate complex analytical findings and recommendations clearly and concisely to both technical and non-technical stakeholders.
• Stay up-to-date with the latest research and advancements in data science, machine learning, and artificial intelligence.
• Build data visualizations and dashboards to monitor key performance indicators and communicate insights effectively.
• Contribute to the development of the company's data strategy and data governance practices.
• Mentor junior data scientists and share knowledge within the team.
• Ensure the ethical and responsible use of data.

• Master's or PhD in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Minimum of 5-7 years of experience in data science, with a proven track record of building and deploying predictive models.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
• Strong experience with SQL and working with large datasets in database environments.
• Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex concepts effectively.
• Experience in the e-commerce industry is highly desirable.
• Ability to work effectively in a hybrid work environment.

• Competitive salary and performance-based bonuses.
• Stock options or employee equity program.
• Comprehensive health, dental, and vision insurance.
• Hybrid work arrangement offering flexibility.
• Generous paid time off and company holidays.
• Access to professional development resources and training.
• Opportunities to work with cutting-edge technologies and large datasets.
• Collaborative and innovative work environment in **Jaipur, Rajasthan**.
• Pension and retirement planning options.
• Regular team lunches and social events.

• Lead the development and deployment of machine learning models, statistical analyses, and predictive algorithms to solve complex business problems.
• Mentor and manage a team of data scientists, providing technical guidance and fostering a collaborative environment.
• Define data science strategies and roadmaps aligned with business objectives.
• Collaborate with stakeholders from various departments (e.g., product, marketing, engineering) to identify opportunities for data-driven solutions.
• Design and conduct experiments to test hypotheses and measure the impact of new features or strategies.
• Clean, transform, and analyze large, complex datasets from various sources.
• Develop and maintain robust data pipelines and infrastructure for analytical workloads.
• Communicate complex findings and insights clearly and effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, and explore their applicability.
• Ensure the ethical and responsible use of data and AI technologies.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with at least 3 years in a leadership or senior role.
• Proven expertise in machine learning algorithms (e.g., regression, classification, clustering, deep learning) and statistical modeling.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
• Strong SQL skills and experience working with large-scale databases and data warehousing solutions.
• Experience with big data technologies (e.g., Spark, Hadoop) is highly desirable.
• Excellent data visualization and storytelling skills.
• Demonstrated ability to lead projects from conception to deployment.
• Strong problem-solving skills and the ability to think critically and creatively.
• Excellent communication, presentation, and interpersonal skills.
• Experience in the fintech industry is a significant plus.

• Design, develop, and implement advanced Machine Learning models and algorithms, with a strong focus on Natural Language Processing (NLP).
• Build and optimize NLP pipelines for tasks such as text classification, named entity recognition, question answering, and summarization.
• Utilize deep learning frameworks (e.g., TensorFlow, PyTorch) to develop and train NLP models.
• Collaborate with data scientists and researchers to translate research findings into production-ready ML systems.
• Deploy and maintain ML models in production environments, ensuring scalability, performance, and reliability.
• Perform data preprocessing, feature engineering, and model evaluation for NLP tasks.
• Stay abreast of the latest advancements in NLP, Machine Learning, and Artificial Intelligence research.
• Write clean, well-documented, and efficient code.
• Participate in code reviews and contribute to technical discussions.
• Troubleshoot and debug complex ML systems.
• Contribute to the development of internal tools and frameworks to streamline ML workflows.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Computational Linguistics, or a related quantitative field.
• 5+ years of experience in Machine Learning, with a significant focus on Natural Language Processing.
• Proven experience in developing and deploying NLP models in production environments.
• Strong proficiency in Python and experience with ML/NLP libraries (e.g., spaCy, NLTK, Hugging Face Transformers, scikit-learn).
• Expertise in deep learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of various NLP techniques, algorithms, and architectures (e.g., RNNs, LSTMs, Transformers).
• Experience with data processing and manipulation for text data.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices is a plus.
• Excellent problem-solving, analytical, and research skills.
• Strong communication and collaboration skills, essential for remote work.
• Ability to work independently and manage projects effectively in a remote setting.

• Lead the design and implementation of advanced machine learning models for healthcare applications, including disease prediction, patient risk stratification, and treatment efficacy analysis.
• Explore, clean, and transform large, complex datasets from various healthcare sources.
• Develop and deploy scalable ML pipelines for real-time inference and batch processing.
• Collaborate with clinicians, researchers, and engineers to understand clinical needs and translate them into data-driven solutions.
• Evaluate and benchmark model performance, ensuring robustness, fairness, and interpretability.
• Stay abreast of the latest advancements in machine learning, artificial intelligence, and their applications in healthcare.
• Mentor junior data scientists and contribute to building a strong data science culture.
• Communicate complex analytical findings clearly and concisely to both technical and non-technical stakeholders.
• Contribute to research publications and present findings at relevant conferences.

• Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Bioinformatics, or a related quantitative field.
• 8+ years of progressive experience in data science, with a significant focus on machine learning applications in the healthcare domain.
• Expertise in building and deploying machine learning models using Python (e.g., scikit-learn, TensorFlow, PyTorch) and associated libraries.
• Strong experience with SQL and NoSQL databases, and data manipulation tools (e.g., Pandas).
• Deep understanding of statistical modeling, hypothesis testing, and experimental design.
• Proven ability to work with large, diverse datasets, including EHR, claims, or genomic data.
• Excellent problem-solving skills and a passion for applying data science to improve health outcomes.
• Strong communication and collaboration skills, with experience working in multidisciplinary teams.
• Demonstrated experience in leading data science projects from conception to deployment.

• Lead a team of data scientists in the design, development, and deployment of machine learning and AI models.
• Identify business opportunities and translate them into data science projects and analytical solutions.
• Perform complex data analysis, feature engineering, and model building using advanced statistical and ML techniques.
• Develop and implement predictive models, classification algorithms, recommendation systems, and other AI-driven solutions.
• Validate and evaluate model performance, ensuring accuracy, scalability, and reliability.
• Collaborate with engineering teams to integrate models into production environments.
• Mentor junior data scientists, providing technical guidance and fostering best practices.
• Stay abreast of the latest advancements in machine learning, AI, and data science.
• Communicate complex findings and insights to stakeholders through clear and concise presentations and reports.
• Contribute to the development of data science methodologies and best practices within the organization.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• 5+ years of experience in data science, with a proven track record in machine learning and AI model development.
• At least 2 years of experience in a lead or supervisory role, mentoring data scientists.
• Strong proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) and database systems (SQL, NoSQL).
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts.
• Experience in defining project requirements and managing data science project lifecycles.
• Familiarity with cloud platforms (AWS, Azure, GCP) for data science workloads is a plus.

• Competitive salary and performance-based bonuses.
• Opportunity to work on challenging and impactful AI/ML projects.
• Leadership role in a dynamic and innovative analytics firm in **Jaipur**.
• Professional development budget for conferences, workshops, and certifications.
• Collaborative team environment with access to industry experts.
• Generous paid time off and company holidays.
• Comprehensive health, dental, and vision insurance.
• Retirement savings plan.
• Potential for profit sharing.
• Access to cutting-edge tools and technologies.