131 Data Scientist Jobs - Page 5

Roles and Responsibilities : Must have skills: Python Programming, Machine Learning, Statistical Analysis, Data Science, Generative AI (GPT, DALLE, GANs), Cloud (AWS/Azure/GCP), Model Deployment, API Development, Docker/Kubernetes Good to have skills: PyTorch, TensorFlow, Large-Scale Data Processing, Cloud Integrations, NLP, Computer Vision, Security Best Practices, Performance Optimization, Open-Source Contributions Experience: Minimum 6-12+ years of experience in Data Science, Machine Learning, or related fields with a focus on Generative AI models (LLMs) and API development. Educational Qualification: Bachelor's or Master’s in Computer Science, Data Science, Statistics, Engineering, or related Analytics discipline from a premier institute. Job Summary: Accenture AI is seeking a talented and motivated Generative AI Data Scientist Analyst to join our Banking team. The ideal candidate will leverage their expertise in Generative AI models, Machine Learning, Data Analysis, and Cloud Platforms to develop innovative solutions and enhance AI capabilities. This role will involve collaborating with cross-functional teams to design, develop, and implement generative AI solutions that meet our business needs. Roles & Responsibilities: Collaboration: Work closely with product managers, engineers, and other stakeholders to understand requirements and deliver impactful AI solutions. Model Deployment: Containerize and deploy generative AI models using tools like Docker, Kubernetes, and cloud platforms (e.g., AWS, Azure, Google Cloud). API Development: Design, develop, and deploy robust APIs to expose generative AI models (e.g., GPT, DALLE, Stable Diffusion, GANs) for integration into client systems and applications. Client Collaboration: Work closely with clients to understand their technical requirements and deliver tailored API solutions that meet their business needs. Generative AI Model Integration: Integrate generative AI models into existing workflows, applications, and platforms via APIs. Performance Optimization: Optimize API performance for latency, scalability, and reliability, ensuring seamless user experiences. Data Pipeline Development: Build and maintain data pipelines to support real-time or batch processing for generative AI models. Security and Compliance: Implement security best practices and ensure APIs comply with data privacy and regulatory standards. Documentation: Create comprehensive API documentation, including usage examples, SDKs, and troubleshooting guides. Testing and Monitoring: Develop automated testing frameworks and monitoring systems to ensure API reliability and performance. Stay Updated: Keep up with the latest advancements in generative AI, API development, and cloud technologies to bring innovative solutions to clients. Professional & Technical Skills: Strong proficiency in Python programming and experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Expertise in API Development and deployment, with hands-on experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Ability to build and optimize data pipelines for generative AI models. Knowledge of security best practices and ensuring compliance with regulatory standards. Strong problem-solving, analytical, and creative thinking skills to design and implement innovative solutions. Excellent communication skills, capable of conveying complex technical concepts to diverse audiences. Additional Information: Experience with large-scale data processing and expertise in NLP or computer vision. Contributions to open-source AI/ML projects. Experience with cloud integrations, big data technologies, and performance optimization. Familiarity with security standards and regulatory compliance in AI solutions

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

About the job Position: Assistant Manager/Manager Credit Risk What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries- Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must.- Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch)- Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus.- Proficient knowledge of cloud platforms (AWS, GCP, Azure).- Strong problem-solving and analytical skills.- Ability to work in team-oriented, collaborative environment. Data Scientist- Statistician- Data Engineer- Python- R- Supervised & Unsupervised learning- Machine Learning Algorithms- Deep Learning- Hugging Face- Natural Language Processing (NLP)- Computer Vision- TensorFlow- PyTorch- Scikit-learn- Transformers- LLM Frameworks- LLM Models- GPT -3, 4o- BERT- Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries- Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch)- Experience with data labeling and annotation tools.- Certifications in cloud platforms or ML technologies can be a plus.- Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills.- Ability to work in team-oriented, collaborative environment. Data Scientist- Statistician- Data Engineer- Python- R- Supervised & Unsupervised learning- Machine Learning Algorithms- Deep Learning- Hugging Face- Natural Language Processing (NLP)- Computer Vision- TensorFlow- PyTorch- Scikit-learn- Transformers- LLM Frameworks- LLM Models- GPT -3, 4o- BERT- Llama

DAZN Group is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Role & responsibilities Architect and implement Al solutions utilizing cutting-edge technologies like LLM, Langchain, and Machine Learning. AIML solution development in Azure using Python Ability to build and finetune the model to improve the performance Create own technology if off-the-shelf technology is not solving the problem. E.g changes to traditional RAG approaches, finetune LLM, create architectures. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Create end to end AI systems with responsible AI principles Preferred candidate profile

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question answering is must. Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) Experience with data labeling and annotation tools. Certifications in cloud platforms or ML technologies can be a plus. Proficient knowledge of cloud platforms (AWS, GCP, Azure). Strong problem solving and analytical skills. Ability to work in team oriented, collaborative environment.Keywords : Data Scientist Statistician Data Engineer Python R Supervised & Unsupervised learning Machine Learning Algorithms Deep Learning Hugging Face Natural Language Processing (NLP) Computer Vision TensorFlow PyTorch Scikit learn Transformers LLM Frameworks LLM Models GPT 3, 4o BERT Llama

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Required Skills & Qualifications: 3-5 years of hands-on experience in data science, machine learning, and statistical modeling. Strong expertise in time series forecasting (ARIMA, XGBoost, RandomForest, TFT, NHITS, etc.) and familiarity with deep learning frameworks (TensorFlow, PyTorch). Excellent programming skills in Python (preferred), with proficiency in libraries such as NumPy, Pandas, scikit-learn, and visualization tools (Matplotlib, Seaborn, Plotly). Solid conceptual understanding of machine learning algorithms, deep learning architectures, and statistical methods. Experience with data preprocessing, feature engineering, and model evaluation. Ability to learn quickly and adapt to new technologies, tools, and methodologies. Strong problem-solving skills and a keen attention to detail. Excellent communication and presentation skills. Preferred Qualifications: Experience with cloud platforms and MLOps tools. Exposure to big data technologies (Spark, Hadoop) is a plus. Masters degree in Computer Science, Statistics, Mathematics, or a related field.

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

: Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Salary : 20 to 35 LPA Exp: 3 to 10 years Location :Bangalore/Pune/Gurugram (Hydrid) Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) PD/LGD model development Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Text classification using any of the following : decision trees, knn classification, support vector machines or LDA Exp on SQL would be a plus

Role & responsibilities We are seeking a skilled AI/ML Engineer proficient in Python to join our dynamic team. In this role, you will collaborate with cross-functional teams to design, develop, and deploy machine learning models and AI systems. You will be responsible for implementing algorithms and workflows that enable our organization to leverage data for insightful decision-making and innovative product solutions. Key Responsibilities:- Develop machine learning models and algorithms using Python and relevant libraries (e.g., Tensor Flow, PyTorch, sci-kit-learn). Min 6 months of experience in Gen AI and Proficiency in could technologies such as AWS, GCP or azure. Collaborate with data engineers to design and implement data pipelines for efficient data processing, analysis, and model training. Apply machine learning techniques to solve complex business problems and optimize existing processes. Evaluate and benchmark different machine learning models to determine optimal solutions. Work closely with product managers and stakeholders to understand business requirements and translate them into technical solutions. • Implement scalable and reliable machine learning infrastructure and productionize models. Stay updated with the latest developments in AI/ML research and apply them to improve our systems continuously. Participate in code reviews, knowledge sharing, and contribute to the overall growth of the AI/ML team. Work from office Afternoon shift NO ONLINE INTERVIEW

Strong programming skills in Python or R, with good knowledge in data manipulation, analysis, and visualization libraries (pandas, numpy, matplotlib, seaborn) Knowledge of machine learning techniques algorithms. FMCG industry will be preferable. Required Candidate profile Hands-on knowledge on machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Proficiency in SQL for data extraction, integration, and manipulation to analyze large datasets. Perks and benefits To be disclosed post interview

Hexaware is conducting Walkin Interview for Data Scientist (Agentic AI) _Chennai Location_ 17th May 25 (Saturday) We urgently looking for Immediate joiners/Early joiners. Interested Candidates can share CV at umaparvathyc@hexaware.com Experience range- 3yrs to 19yrs Notice period- 15 days/30days Max Interview Location (Face to Face)- Chennai Open Positions: 1. AI Engineer -3+yrs 2. Lead Agentic AI Developer -5+yrs 3. Data scientist Architect- 10_yrs MUST HAVE: Must have Experience: Agentic AI, LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Knowledge of Agentic AI concepts and applications 2. Strong Experience in Data Scientist (GENAI) 3. Proficiency with Generative AI models like GANs, VAEs, and transformers 4. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 5. Strong Python Fast API experience, SDA based implementations for all the APIs

We are looking for a Data Scientist with a product engineering mindset to join our fast-paced, data-driven team. Youll work at the intersection of data science, software engineering, and product development, helping to design and deliver scalable, data-centric solutions that drive business value and enhance user experience, particularly in the sports domain. Collaborate with cross-functional teams (Product, Engineering, Design, and Business) to identify opportunities where data science can improve products and services. Design, develop, and deploy machine learning models and data pipelines in production environments using Python, R, and cloud-native services on AWS and Microsoft Azure. Translate complex data into clear product insights and actionable recommendations. Contribute to the product lifecycle by embedding data science into product discovery, experimentation, and iterative improvements. Maintain a strong focus on the user experience, ensuring data-driven solutions are practical and aligned with product goals. Communicate findings effectively with both technical and non-technical stakeholders. Location: Delhi, Mumbai, Bengaluru, Hyderabad, Kolkata, Pune, Chennai, Remote

Prescience Decision Solutions is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Prescience Decision Solutions is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams