131 Data Scientist Jobs

Requirement : Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field. Knowledge of R, or Python Knowledge of building regression and classification models Familiarity with any or all of, Regularization methods: Lasso, Ridge Ensemble methods: Random Forest, Boosting Time Series analysis: Auto-regression, moving average, etc. Graphs modeling Support Vector Machines Decision trees Preferred : Master's or higher degrees. Industry experience in the field of Data Science. Participation in competitions like Kaggle, Netflix Data Challenge. Open source contributions in areas of Data Science (Machine Learning, Deep Learning, Statistical Learning). Worked on Scala and/or Spark. Understanding of generative AI concepts, such as transformers, diffusion models, and LLMs

Job Position : Principal Data Scientist / Sr Data Scientists /Data Scientist / Jr. Data Scientist / Data Science Intern / Machine Learning Engineer-Global Tech AI Health Startup. Joining : Immediately. Job Location : Delhi NCR, India. Global HQ, Benovymed Global Technology Development and Innovation Center & Benovymed Global R and D, and AI Health Innovation Center in Delhi NCR. Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems. CTC : - Best Package in Industry. - Terms & Conditions Apply as per our organization. - To deserving eligible candidates only, the company Equity / ESOP may be given also as a part of a Package for a long-term career opportunity. - Apply with your CV with passport size photo, & current CTC, expected CTC, Notice Period, Project details & cover letter.

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.

Notice Period: Maximum 30 days Location: Bangalore, Chennai, Kolkata, Pune, and Hyderabad Note: Candidates based in Hyderabad must attend in-person interviews for the second round. Role Summary: Generative AI Specialist Mandatory Skills: Gen AI, LLMs, ML/DL/NLP, RAG, LangChain, Mistral, LLaMA, Hugging Face, Python, TensorFlow, PyTorch, Django, Vector DBs Preferred Skills: GCP/Azure/AWS, Databricks, MLOps (e.g., Kubeflow, MLflow), Kubernetes, GitHub/Bitbucket, Azure DevOps, GPT-4 Responsibilities: Design, develop, and deploy generative AI solutions using modern ML/DL techniques. Work with large-scale datasets; handle preprocessing and model optimization. Build applications using LLMs and frameworks like LangChain, leveraging models like Mistral, LLaMA, GPT-4. Research and implement cutting-edge GenAI algorithms and architectures. Ensure Responsible AI compliance and monitor model performance post-deployment. Collaborate with cross-functional teams for solution integration and data engineering. Drive innovation by staying up to date with AI trends. Provide technical leadership, mentorship, and contribute to project governance and stakeholder communication. If you meet the requirements and are looking for a new opportunity, we'd love to hear from you! Interested candidates can send their resumes to admin@spearheadps.com OR Contact us via call/WhatsApp at 9899080360

Responsibilities : - Transform raw and unstructured data into structured, actionable formats for analysis and reporting. - Write, optimize, and maintain SQL queries and stored procedures to ensure efficient data retrieval and processing. - Design and implement complex SQL queries, including Common Table Expressions (CTEs), window functions, recursive queries, dynamic pivoting and joins, to extract actionable insights from large datasets efficiently. - Design, develop, and maintain databases and data pipelines to support analytics and reporting needs. - Perform data engineering tasks, including data ingestion, cleaning, and preprocessing. - Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights. - Develop and implement machine learning (ML) models and natural language processing (NLP) solutions to solve business challenges. - Build and monitor key performance indicators (KPIs) for dashboards and reporting tools. - Create wireframes and collaborate with stakeholders to design intuitive data visualizations and dashboards. - Ensure data integrity and perform quality checks to maintain high standards of accuracy and reliability. - Collaborate with cross-functional teams to align data initiatives with business goals. - Manage data science projects from ideation to deployment, ensuring timely delivery and measurable impact. - Communicate findings and insights effectively through presentations and reports to technical and non-technical audiences/ stakeholders. - Utilize statistical modelling and data mining techniques to drive decision-making and strategy. Must-Have Skills : - Proficiency in SQL and Python/R for data manipulation and analysis. - Experience with Machine Learning (ML) and NLP techniques. - Strong understanding of EDA and statistical modelling. - Hands-on experience with Google Cloud Platform (GCP) and Vertex AI. - Excellent communication and presentation skills. - Solid grasp of data engineering principles, including ETL processes. Good-to-Have Skills : - Knowledge of data mining techniques. - Knowledge of generative AI tools and frameworks for tasks such as synthetic data generation and data augmentation. - Familiarity with dashboard wireframe creation tools and methods. - Ability to build or derive KPIs for visualization dashboards. - Expertise in Excel for advanced calculations and analysis. - Background in project management, including Agile or similar methodologies. - Experience in cross-functional team collaboration. - Hands-on experience fine-tuning or deploying pre-trained Gen AI models (e.g., Hugging Face Transformers, OpenAI APIs)

Work Location : Hyderabad/ Bangalore Working Hours : 2PM to 11PM IST Mid-Level ML Engineers / Data Scientist Role : (4-5 years of experience ) - Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data using Pandas and PySpark - Experience with statistical analysis, data modeling, machine learning, optimizations, regression modeling and forecasting, time series analysis, data mining, and demand modeling. - Experience applying various machine learning techniques and understanding the key parameters that affect their performance. - Experience with Predictive analytics (e.g., forecasting, time-series, neural networks) and Prescriptive analytics (e.g., stochastic optimization, bandits, reinforcement learning). - Experience with Python and Python packages like NumPy, Pandas and deep learning frameworks like TensorFlow, Pytorch and Keras - Experience in Big Data ecosystem with frameworks like Spark, PySpark , Unstructured DBs like Elasticsearch and MongoDB - Proficiency with TABLEAU or other web-based interfaces to create graphic-rich customizable plots, charts data maps etc. - Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL). - Previous experience in ML, data scientist or optimization engineer role with a large technology company. - Experience in an operational environment developing, fast-prototyping, piloting, and launching analytic products. - Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations. - Experience in creating data driven visualizations to describe an end-to-end system. - Excellent written and verbal communication skills. The role requires effective communication with colleagues from computer science, operations research, and business backgrounds. - Bachelors or Masters in Artificial Intelligence, Computer Science, Statistics, Applied Math, or a related field.

Job Title : AI Engineer - Azure AI. Key Responsibilities : We are seeking a highly skilled and motivated AI Engineer to join our team. In this role, you will leverage your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions that enhance business processes and deliver value to our clients. Candidates must have extensive experience in the Microsoft environment. You will collaborate with cross-functional teams to create innovative solutions using Microsoft tools and platforms. Responsibilities : Agent Development : - Design, implement, and optimize AI agents using Microsoft Azure Framework and related technologies. - Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration : - Deploy AI solutions within client environments, ensuring scalability and seamless integration with existing systems. - Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation : - Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. - Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support : - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. - Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement : - Stay updated on advancements in AI, machine learning, and Microsofts AI technologies. - Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills : - Strong knowledge of Azure OpenAI, Azure AI Search Index and open source libraries such as LangChain and LlamaIndex. - Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. - Understanding of conversational AI technologies and chatbot frameworks. - Experience with data analysis tools and techniques to uncover insights and optimize models. Requirements : - Bachelors or Masters degree in Computer Science, Data Science, or a related field. - Proven experience in developing and deploying AI/ML models in real-world applications. - Strong programming skills, especially in Python, and familiarity with version control systems like Git. - Extensive experience in the Microsoft environment and related technologies.

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 : 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.

Responsibilities : Data Exploration and Insights : - Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution. - This includes working with large datasets from various sources, including Excel files and databases. Data Quality Improvement : - Perform various analyses specifically aimed at improving data quality within the SCI system. - This will involve identifying data quality issues, proposing solutions, and implementing improvements. Weekly Playback and Collaboration : - Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis. - Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks. Project Scaling and Support : - Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets. - This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records. Data Analysis and Validation : - Perform thorough data analysis and validation of SCI records after batch ingestion. - Proactively identify insights and implement solutions to improve data quality. Stakeholder Collaboration : - Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention. - Communicate findings and recommendations clearly and effectively. Technical Requirements : - 5+ years of experience as a Data Scientist. - Strong proficiency in Python and SQL. - Extensive experience using Jupyter Notebook for data analysis and visualization. - Working knowledge of data matching techniques, including fuzzy logic. - Experience working with large datasets from various sources (Excel, databases, etc. - Solid understanding of data quality principles and methodologies. Skills : - SQL - Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included) - Data Analysis - Jupyter Notebook - Data Cleansing - Fuzzy Logic - Python - Data Quality Improvement - Data Validation - Data Acquisition - Communication and Collaboration - Problem-solving and Analytical skills Preferred Qualifications (Optional, but can help attract stronger candidates) : - Experience with specific data quality tools and techniques. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI). - Knowledge of statistical modeling and machine learning algorithms

Job Title : Data Scientist - AI Integration & Orchestration. Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Data Scientist Responsibilities : Data Exploration and Insights : - Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution. - This includes working with large datasets from various sources, including Excel files and databases. Data Quality Improvement : - Perform various analyses specifically aimed at improving data quality within the SCI system. - This will involve identifying data quality issues, proposing solutions, and implementing improvements. Weekly Playback and Collaboration : - Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis. - Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks. Project Scaling and Support : - Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets. - This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records. Data Analysis and Validation : - Perform thorough data analysis and validation of SCI records after batch ingestion. - Proactively identify insights and implement solutions to improve data quality. Stakeholder Collaboration : - Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention. - Communicate findings and recommendations clearly and effectively. Technical Requirements : - 5+ years of experience as a Data Scientist. - Strong proficiency in Python and SQL. - Extensive experience using Jupyter Notebook for data analysis and visualization. - Working knowledge of data matching techniques, including fuzzy logic. - Experience working with large datasets from various sources (Excel, databases, etc. - Solid understanding of data quality principles and methodologies. Skills : - SQL - Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included) - Data Analysis - Jupyter Notebook - Data Cleansing - Fuzzy Logic - Python - Data Quality Improvement - Data Validation - Data Acquisition - Communication and Collaboration - Problem-solving and Analytical skills Preferred Qualifications (Optional, but can help attract stronger candidates) : - Experience with specific data quality tools and techniques. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI). - Knowledge of statistical modeling and machine learning algorithms

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.

Responsibilities : Data Exploration and Insights : - Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution. - This includes working with large datasets from various sources, including Excel files and databases. Data Quality Improvement : - Perform various analyses specifically aimed at improving data quality within the SCI system. - This will involve identifying data quality issues, proposing solutions, and implementing improvements. Weekly Playback and Collaboration : - Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis. - Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks. Project Scaling and Support : - Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets. - This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records. Data Analysis and Validation : - Perform thorough data analysis and validation of SCI records after batch ingestion. - Proactively identify insights and implement solutions to improve data quality. Stakeholder Collaboration : - Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention. - Communicate findings and recommendations clearly and effectively. Technical Requirements : - 5+ years of experience as a Data Scientist. - Strong proficiency in Python and SQL. - Extensive experience using Jupyter Notebook for data analysis and visualization. - Working knowledge of data matching techniques, including fuzzy logic. - Experience working with large datasets from various sources (Excel, databases, etc. - Solid understanding of data quality principles and methodologies. Skills : - SQL - Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included) - Data Analysis - Jupyter Notebook - Data Cleansing - Fuzzy Logic - Python - Data Quality Improvement - Data Validation - Data Acquisition - Communication and Collaboration - Problem-solving and Analytical skills Preferred Qualifications (Optional, but can help attract stronger candidates) : - Experience with specific data quality tools and techniques. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI). - Knowledge of statistical modeling and machine learning algorithms

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

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.

Joining : Immediately. Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems.

Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Hybrid (Bengaluru) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Alphametricx) (*Note: This is a requirement for one of Uplers' client - Technology, Information and Media) What do you need for this opportunity? Must have skills required: Cision, Experience in deploying machine learning models in production environments., Experience with media monitoring, Familiarity with media intelligence tools such as Meltwater, or media analytics platforms., or similar., Social Listening, Data Scientist, NLP Technology, Information and Media is Looking for: Job Title: Senior Data Scientist Location: Bangalore Job Type: Full-time Experience Level: Senior Client is hiring for the role of Senior or Lead Data Scientist Position to drive the business growth of our Analytics COE. We are looking at the aspirant with a proven track record of solutioning & delivering NLP solutions to Fortune 500 companies. This individual will be responsible for building unique solutions and also deliver based on the set SLAs Job Summary: As a Senior Data Scientist, you will lead the development and optimization of advanced analytics tools, with a focus on media intelligence solutions. Your work will involve analyzing large data sets from various media channels, designing algorithms to track trends, and providing actionable insights. We are looking for someone with a strong background in building media analytics or intelligence tools, combined with excellent problem-solving skills and a passion for innovation. Key Responsibilities: Lead the design and development of analytics platforms and media intelligence tools, transforming large, unstructured data into meaningful insights. Develop machine learning models for trend detection, sentiment analysis, keyword extraction, and content recommendation. Work with large-scale media data from sources such as social media, news, blogs, and other online platforms. Collaborate with cross-functional teams, including data engineers, software developers, and product managers, to deliver end-to-end solutions. Implement NLP techniques to analyze and categorize media content from multiple sources. Build and optimize data pipelines for efficient data processing, storage, and retrieval. Translate business objectives into data-driven solutions and deliver actionable insights to internal teams and clients. Mentor and guide junior data scientists, providing support in developing their technical skills and career growth. Stay updated on the latest trends in data science, AI, and media intelligence to ensure the tools and platforms remain at the cutting edge. Required Skills and Qualifications: Proven experience (7+ years) as a Data Scientist, preferably in the media intelligence or analytics tool development domain. Strong expertise in machine learning, NLP, and statistical modeling. Hands-on experience with media data analysis, including sentiment analysis, keyword analysis, and audience engagement tracking. Proficiency in Python, R, and SQL. Familiarity with big data tools such as Hadoop, Spark, Redis, Apache Flink, and cloud platforms (AWS, GCP, Azure). Strong understanding of data pipelines and experience with data processing frameworks. Ability to work with large, unstructured data sets and develop models that derive actionable insights. Excellent problem-solving skills and the ability to deliver solutions in a fast-paced environment. Strong communication and presentation skills, with the ability to explain complex data insights to non-technical stakeholders. A Master's or PhD in Data Science, Computer Science, Statistics, or a related field. Preferred Skills: Experience with media monitoring, social listening, or media analytics platforms. Experience in deploying machine learning models in production environments. Familiarity with media intelligence tools such as Meltwater, Cision, or similar. Benefits: Competitive salary and bonus structure. A collaborative work environment with access to cutting-edge technologies.

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 Role : We are seeking a highly skilled and passionate Senior Data Scientist to join our growing AI/ML team. In this role, you will play a crucial part in developing cutting-edge AI solutions within the healthcare domain. You will focus on building and refining sophisticated Large Language Models (LLMs) to address critical challenges and improve healthcare outcomes. Key Responsibilities : - Develop and refine LLMs tailored for specific healthcare applications (e.g., medical diagnosis, drug discovery, patient care). - Design and implement robust data pipelines for collecting, cleaning, and preparing high-quality healthcare datasets for LLM training. - Conduct thorough experimentation with different LLM architectures, hyperparameters, and training techniques. - Fine-tune pre-trained LLMs on specific healthcare tasks and datasets. - Implement techniques for improving LLM performance, such as prompt engineering, few-shot learning, and reinforcement learning. - Develop and implement rigorous evaluation metrics to assess the performance of LLMs on various healthcare tasks. - Conduct thorough model validation and testing to ensure accuracy, reliability, and safety. - Monitor model performance in production and identify areas for improvement. - Stay abreast of the latest advancements in LLM research and development. - Explore and implement cutting-edge techniques in natural language processing (NLP) and machine learning. - Conduct research and development on novel applications of LLMs in the healthcare domain. - Collaborate effectively with data engineers, clinicians, researchers, and other stakeholders. - Clearly communicate complex technical concepts to both technical and non-technical audiences. - Present research findings and project updates to team members and stakeholders. Qualifications : Essential : - Master's or Ph.D in Computer Science, Artificial Intelligence, Machine Learning, or a related field. - 3+ years of experience in developing and deploying machine learning models, with a strong focus on NLP and deep learning. - Proven experience in building and fine-tuning large language models. - Strong proficiency in Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch). - Experience with data preprocessing, feature engineering, and model evaluation techniques. - Excellent analytical and problem-solving skills. - Strong communication and interpersonal skills

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 : 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.

Marketing Data Scientist Role Summary IMEA Regional Marketing is looking for a talented and highly motivated individual to join our team in the role of Marketing Data Scientist. In this role, you will work with marketing and performance managers on translating complex data findings into useful insights that guide decision-making and future marketing investment. You will be responsible for providing useful insights, recommendations, and measurements of marketing campaigns that will drive innovation and efficiency gains for the business. The candidate will define and execute data-driven, analytical solutions to engage our customers and help solve commercial problems. This role is not about crunching numbers, its about finding compelling insights within data and using your exceptional business and communications skills to translate those insights into action. As one of the masterminds behind our data-driven campaign planning, forecasting and analysis, youll spend your time digging into big, complex data sets, customer touch points and journeys. The data will not remain inert in your hands, however, since you’ll use your critical thinking, problem solving and communication skills to influence and drive thoughtful and well-informed decision making with marketing and business leaders. You will work closely with the Campaign Leads and Marketing Managers to create insights that shape the campaign strategy of our product and solutions, optimize content, and assess the impact of various initiatives. You will also be responsible for surfacing key business insights and recommendations in campaign planning and reviews. Our team of entrepreneurial, enthusiastic, and customer-centric marketeers are helping global and customers in the Indian subcontinent, Middle East, and sub-Saharan Africa integrate their domestic and international supply chains to reach their end-customers. You will have the opportunity to partner with marketing, sales, revenue operations, and finance to develop strategies and analytics designed to enable informed decision making and lead efforts to identify gaps in our data to better drive engagement, client acquisition, retention, and revenue. Working in close collaboration with a diverse and dynamic team of colleagues around the world, you will be part of setting the direction for our regional marketing team and collaborating across the organization to measure impact performance on all marketing activations. REQUIRED COMPETENCIES AND SKILLS: Basic Qualifications: Bachelor’s degree is required with emphasis on analytical skills – e.g. E-commerce, Data Science, Statistics, Business, Computer Science, or equivalent practical experience 5 years of experience in a Marketing Operations, Demand Generation, Data Planner, or related role, ideally at a B2B technology company or agency. Demonstrated proficiency in analytical work in marketing/sales, or a business operations and analytics environment, including analyzing data with spreadsheet software (e.g. Excel Sheets) and database query (e.g. SQL) experience Champion of data and visualization with strong, effective presentation and story-telling skills. Demonstrated ability to conduct sophisticated and creative analysis to solve business problems and translate the results into actionable deliverables, clearly-written summaries/presentations, and region-wide communications. Power BI experience and/or related business intelligence tools is highly preferred. Experience with marketing analytics platforms like Google Analytics is a plus CRM: Salesforce Sales Cloud experience with explicit knowledge of leads flow process, data hygiene and reporting dashboards Strong skills in data analysis, statistics, programming (e.g. SQL, R or Python) Strong stakeholder management skills and ability to manage interfaces at all levels in the organisation Strong verbal and written communications skills and ability to articulate complex insights to cross-functional audiences. Digitally savvy. Preferred Qualifications: Experience with marketing analysis and data-backed customer segmentation is a plus. Understanding of digital marketing, digital logistics platforms, and solutions. Business acumen and communication skills; proficiency in translating data into actionable insights and digestible formats for the business. Highly organized with multi-tasking skills; efficient in ambiguous situations. Demonstrated ability to work across organizational boundaries. Knowledge about digital campaign landscape, cloud computing market and technologies Your personality Strong results orientation with a proven track record of flawless execution and strong attention to detail Demonstrated flexibility, creativity and problem-solving skills Comfortable working in a demanding, fast-paced changing environment that is going through high growth Self-motivated, enthusiastic, and organized. Independent contributor and self-starter who takes ownership of assignments and sees them to completion A collaborator who can work across diverse teams and build rapport to gain the trust and confidence from local and international stakeholders. Hands-on, can-do attitude, and willing to propose and try new things Complete integrity with sensitive and confidential information Curious by nature, motivated by learning and by taking on challenges Approachable and social – we’re a colorful and diverse team with big ambitions, high energy who also has plenty of fun along the way Great organizational skills and attention to detail; able to execute and prioritize multiple tasks simultaneously. Team player, but ability to work independently and be a self-starter. Responsibilities: This is a hands-on position; the ideal candidate must be willing to roll-up their sleeves and work directly with large datasets, conduct data analysis, build self-service reporting tools and dashboards in an environment of rapid growth and increasing complexity, and communicate complex business insights in a clear and precise manner. The candidate must be a self-starter with a bias towards independent problem solving, a passion for identifying and eliminating bottlenecks, and has the foresight to anticipate business needs, make tradeoffs, and balance business dynamics despite constraints. The ideal candidate must also earn trust through performance and relationship building, think analytically about business challenges, and have experience in marketing campaign management. Support the full spectrum of regional marketing data analytics activities Monitor and forecast marketing and sales trends as well as analyze customer and prospect data and downstream funnel performance using Salesforce, Power BI, and other tools Deep dive into data to investigate trends, topical issues, uncover insights, and explore new opportunities for our business growth. Analyse small to large and complex data sets using a variety of tools such as Google Analytics, Salesforce Einstein Analytics, SQL , R and BI tools Use CRM tool to track performance and analyze data against monthly goals Integrate emerging technologies (AI-powered tools..etc ) with marketing platforms to: Build and deploy predictive models to forecast customer behaviour, sales trends, and marketing campaign outcomes. Develop custom scripts or tools to automate routine marketing analysis tasks Cross-channel attribution and multi-touchpoint analysis – develop multi-touchpoint attribution models to understand the impact of various marketing channels on conversion. Works closely with marketing teams to develop dashboards, extract and analyze data, find opportunities, and develop solid recommendations to increase and optimize campaign performance Examine campaign return on investment and conduct demand waterfall analysis to improve profitability of campaigns and performance throughout the sales funnel Utilise data-driven insights to enable leadership to optimize budget and resource allocation Understand how data, and content should be used to optimize conversion rates for a digital experience Identify gaps and pioneer new ways to optimize campaign planning and execution and improve data integrity. Help develop and deliver analytics or measurement frameworks that foster a Test & Learn culture Assist in the development of a structure for managing data analysis requests that can be scaled and improved upon ongoing; e.g. automating ongoing BAU reporting Prepare reports and present results to internal collaborators and management Contribute to the Regional Head of Marketing reporting cadence to ensure weekly, monthly, and quarterly reports are completed to meet timelines with data accuracy Facilitate adoption of the reporting standards by consistently applying them in daily work and educating end users on applicable usage/interpretation of different methodologies Partner with internal regional and global stakeholders from cross-functional and products teams, data engineers to capture business requirements, shape data, and set up processes to design and build reporting solutions.

The AI Engineer with GenAI expertise is responsible for developing advanced technical solutions, integrating cutting-edge generative AI technologies. This role requires a deep understanding of modern technical and cloud-native practices, AI, DevOps, and machine learning technologies, particularly in generative models. You will support a wide range of customers through the "Ideation to MVP" journey, demonstrating proficiency in leading projects and ensuring delivery excellence. Key Responsibilities : Technical & Engineering Leadership : - Develop solutions leveraging GenAI technologies, integrating advanced AI capabilities into cloud-native architectures to enhance system functionality and scalability. - Lead the design and implementation of GenAI-driven applications, ensuring seamless integration with microservices and container-based environments. - Create solutions that fully leverage the capabilities of modern microservice and container-based environments running in public, private, and hybrid clouds. - Contribute to HCL thought leadership across the Cloud Native domain with an expert understanding of open-source technologies (i.e., Kubernetes/CNCF) and partner technologies. - Collaborate on joint technical projects with partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware. Mandatory Skills & Experience. : - A passionate developer with 7+ years of experience in Java, Python, and Kubernetes, comfortable working as part of a paired/balanced team. - Extensive experience in software development, with significant exposure to AI/ML technologies. - Expertise in GenAI frameworks : Proficient in using GenAI frameworks and libraries such as LangChain, OpenAI API, and Hugging Face Transformers. - Prompt engineering : Experience in designing and optimizing prompts for various AI models to achieve desired outputs and improve model performance. - Strong understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models. - Proven experience developing complex solutions that leverage cloud-native technologies-featuring container-based, microservices-based approaches; based on applying 12-factor principles to application engineering. - Exemplary verbal and written communication skills (English). - Positive and solution-oriented mindset. - Solid experience delivering Agile and Scrum projects in a Jira-based project management environment. - Proven leadership skills and the ability to lead projects to ensure delivery excellence. Desired Skills & Experience : - Machine Learning Operations (MLOps) : Experience in deploying, monitoring, and maintaining AI models in production environments using MLOps practices. - Data engineering for AI : Skilled in data preprocessing, feature engineering, and creating pipelines to feed AI models with high-quality data. - AI model fine-tuning : Proficiency in fine-tuning pre-trained models on specific datasets to improve performance for specialized tasks. AI ethics and bias mitigation : - Knowledgeable about ethical considerations in AI and experienced in implementing strategies to mitigate bias in AI models. Knowledgeable about vector databases, LLMs, and SMLs, and integrating with such models. - Proficient with Kubernetes and other cloud-native technologies, including experience with commercial Kubernetes distributions (e., Red Hat OpenShift, VMware Tanzu, Google Anthos, Azure AKS, Amazon EKS, Google GKE). - Deep understanding of core practices including DevOps, SRE, Agile, Scrum, Domain-Driven Design, and familiarity with the CNCF open-source community. - Recognized with multiple cloud and technical certifications at a professional level, ideally including AI/ML specializations from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat. Verifiable Certification : At least one recognized cloud professional / developer certification (AWS/Google/Microsoft).