131 Data Scientist Jobs - Page 4

Job Title: Data Scientist Experience: 8+Years Location: Remote Employment Type: Full-Time Shift Timing: 4 hours overlap with PST timings Job Description : Job Summary: What does a Data Scientist do? As a data scientist, you will be responsible for analyzing and interpreting complex data sets to identify patterns and insights. You will be developing data models and algorithms to support the project needs. Implement data validation strategies to ensure high data quality. Collaborate with AI/ML engineers to integrate data models into the conversion engine system. Present findings and recommendations to stakeholders and management. Not being afraid to fail fast is one of the essential tools an NL Data Scientist can have in the cutting-edge technology market. What you will do: Develop AI-Driven Data Conversion Application : Utilize AI technologies to develop a comprehensive data conversion application. Data Mapping : Implement AI algorithms for accurate data mapping from source to target. Code Generation : Automate code generation using AI models. Data Validation : Apply AI-driven validation techniques to ensure data integrity and quality. Code Conversion : Facilitate seamless code conversion using AI algorithms. Collaboration : Work with data engineers, software developers, AI solution engineers, and business analysts to integrate the data conversion application. Monitor and Troubleshoot : Continuously monitor and troubleshoot the AI-driven application to ensure optimal functionality. Documentation : Maintain detailed documentation of methodologies and processes used in the application development. Stay Updated with Technologies : Keep up-to-date with the latest AI, data science, and data conversion technologies to enhance the application. What you will need to have: Bachelors or Master’s Degree in Data Science, Computer Science, Artificial Intelligence, or a related field. Proficiency in Programming Languages such as Python, SQL, and other relevant languages. Experience with AI/ML Frameworks like TensorFlow, PyTorch, or similar. Knowledge of Data Mapping Techniques : Experience with AI-driven tools and methodologies for data mapping. Strong Code Generation Skills : Experience in developing AI models for automating code generation. Experience with Data Validation : Implementing AI-based validation techniques. Familiarity with Code Conversion : Understanding AI algorithms for code conversion. Experience with Databases like SQL Server and MongoDB. Collaboration Skills : Ability to work effectively with cross-functional teams. Problem-Solving Skills : Strong ability to identify issues and develop creative solutions. Attention to Detail : Ensure accuracy and reliability of data conversions. 5+ Years of Relevant Experience in data science or a related field. Willingness to Fail Fast and learn from mistakes in the fast-paced technology market. Preferred qualifications for consideration: Experience in the Financial Services Industry and an understanding of compliance standards. Certification in Data Science or AI/ML . Experience with Master data management, Data Wrangling and ETL Processes . Familiarity with DevOps Tools like Jira, Confluence, and BitBucket. Experience with data and AI/ML Technologies : Such as NLP/NLU, Azure Cognitive Services, Azure Synapse Analytics, Azure data bricks and Azure ML service. Previous Experience Delivering AI Solutions for complex data or conversions : Seamless Data Schema Conversion, AI-Driven Data Validation for Migration Accuracy, Intelligent Code Generation for Data Transformation Scripts , Historical Data Transformation and Archiving, Intelligent Error Detection and Correction, AI-Augmented Data Reconciliation

About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models,algorithms and systems to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas Theoretical understanding and practise of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Support the team in maintaining machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Participate in monitoring the performance of machine learning models, gaining experience in using statistical methods for evaluation. Working with the Data Platforms teams for understanding and collecting the data. Conduct performance testing, troubleshooting and tuning as required. Stay current with the latest research and technology and communicate your knowledge throughout the enterprise. Qualifications & Experience Master s/PhD in Computer Science, Mathematics, Statistics/related fields or 1+ years of relevant industry experience with a Bachelor s degree. Proficiency in Python or one other high-level programming language. Theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc. Strong written and verbal communication skills Intellectual curiosity and enthusiastic about continuous learning Experience developing machine learning models in Python, or equivalent programming language. Basic familiarity with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. Introductory understanding of statistics as it applies to machine learning. Ability to manage and prioritize your workload and support his/her manager. Experience with SQL and/or NoSQL databases. If you are an exceptional candidate, write in. We are happy to hire you even if you don't have the certified qualifications. Nice to Have: Publications or presentations in recognized Machine Learning and Data Science journals/conferences. Experience with ML orchestration tools (Airflow, Kubeflow or MLFlow) Exposure to GenAI models.

Key Skills : MySQL, Data Scientist, Data Scientist R Programming, Python Roles and Responsibilities: Collaborate with business areas within Asset Management to identify opportunities for enhancing commercial performance and operational efficiency using Analytics and Data Science. Engage with the Data Architecture function to ensure optimal data sources are used in your analytics and data science projects. Design and implement data engineering pipelines for data retrieval and transformation. Create insightful visualisations to share the findings from your analytical work with stakeholders. Develop Artificial Intelligence / Machine Learning models to address different business problems ranging from client retention, risk monitoring, and global portfolio management tasks. Act as a champion for data science, guiding business users and other analysts on analytical techniques, tools, and technologies. Skills Required: Proficiency in Python, PySpark, R, and SQL programming languages. Knowledge of visualisation tools like Tableau (preferred), Qlik, or Power BI. Hands-on experience with Machine Learning using platforms like Jupyter Notebooks. Experience with cloud service providers like Google Cloud, AWS, and Microsoft Azure. Strong analytical skills, with an ability to bring structure and clarity to poorly-defined problems. Stellar interpersonal skills, with an ability to develop strong relationships with stakeholders. Education: Bachelor's degree in related field

Role & responsibilities Title: Data Scientist Experience : 5+ Years Notice Period : 0-15 Days Position: Permeant Work Location: Bangalore(Hybrid) We are seeking a 4-year skilled Data Scientist proficient in Python and R to join our team. The ideal candidate will have extensive experience developing machine learning and statistical models for regression, classification, and time series problems. Additionally, they will have a strong understanding of software engineering principles and the ability to write clear, well-structured, and testable code. Key Responsibilities: Develop machine learning and statistical models for various business needs, including regression, classification, and time series analysis. Implement models using Python and relevant libraries such as scikit-learn, pandas, and numpy. Apply machine learning techniques such as Linear Regression, Random Forest, Classification, and Ensemble methods. Convert R code to Python and ensure seamless integration between the two languages. Utilize R for data manipulation and analysis using tidyverse, dplyr, and data.table. Optimize and enhance existing R code for performance and scalability. Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions. Follow best practices in software engineering to produce clean, manageable, and testable code. Stay updated with the latest industry trends and advancements in data science and machine learning. Required Skills and Qualifications: Bachelors or masters degree in computer science, Statistics, Data Science, or a related field. 6+ years of IT experience with a min of 3+ years in Data Science (AI/ML) Proven experience as a Data Scientist or similar role with hands-on experience in Python and R. Strong knowledge of machine learning algorithms and statistical modeling techniques. Proficiency in Python libraries such as scikit-learn, pandas, numpy, and matplotlib. Expertise in R programming, particularly with tidyverse, dplyr, tidymodels, and data.table. Experience with relational databases and SQL. Ability to convert R code to Python efficiently. Familiarity with software engineering principles and best practices. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Ability to manage multiple projects and meet deadlines. Preferred candidate profile IT background with who willing to relocate from anywhere India to Bangalore location if you are interested please share CV : Mail ID: mounika.c@configusa.com

Analyze customer behavior, pricing models & conversion funnels Identify inefficiencies in fulfillment, logistics & Customer Acquisition Cost (CAC) to improve margins Build & maintain automated dashboards & self-serve analytics tools Required Candidate profile 3-5+ years’ experience in growth analytics, e-commerce analytics, or D2C consulting roles Understanding of SQL and BI tools

Role : Senior ML Engineer Location : Bangalore, Pune Experience : 4 - 7 Yrs Employment Type : Full Time, Permanent Working mode : Regular Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team. Benefits : - Competitive salary and benefits package. - Opportunities for professional growth and development. - Collaborative and supportive work environment.

Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team.

Data Scientist Job Description Job Title: Data Scientist Department: Data Science / Analytics / AI Location: Hyderabad (On-site) Employment Type: Full-time Job Summary We are seeking a highly skilled Data Scientist to analyze complex data, develop predictive models, and generate actionable insights to drive business decisions. The ideal candidate will have strong expertise in statistics, machine learning, and programming , along with the ability to communicate findings effectively to stakeholders. Key Responsibilities 1. Data Analysis & Exploration Collect, clean, and preprocess large datasets from multiple sources. Perform exploratory data analysis (EDA) to uncover trends, patterns, and anomalies. Apply statistical methods to interpret data and validate hypotheses. 2. Machine Learning & Predictive Modeling Design, train, and deploy machine learning models (supervised/unsupervised learning). Optimize model performance through feature engineering, hyperparameter tuning, and validation techniques. Implement algorithms for classification, regression, clustering, recommendation systems, etc. 3. Data Visualization & Reporting Create dashboards and visualizations using tools like Tableau, Power BI, or Matplotlib/Seaborn . Prepare reports and presentations to communicate insights to technical and non-technical stakeholders. 4. Big Data & Cloud Technologies Work with big data tools like Spark, Hadoop, or Databricks for scalable data processing. Deploy models on cloud platforms ( AWS, GCP, Azure ) using ML services like SageMaker, Vertex AI, or MLflow. 5. Collaboration & Business Impact Partner with cross-functional teams (engineering, product, marketing) to integrate data-driven solutions. Translate business problems into analytical frameworks and provide data-backed recommendations. 6. Continuous Learning & Innovation Stay updated with the latest advancements in AI/ML, NLP, deep learning, and generative AI. Experiment with new tools and techniques to improve data science workflows. Required Skills & Qualifications Technical Skills Programming: Python (NumPy, Pandas, Scikit-learn), R, SQL Machine Learning: Regression, Classification, Clustering, NLP, Deep Learning (TensorFlow/PyTorch) Data Tools: Jupyter Notebooks, Git, Docker, Apache Spark Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra) Cloud Platforms: AWS/GCP/Azure (S3, BigQuery, Redshift) Visualization: Tableau, Power BI, Matplotlib, Plotly Soft Skills Strong analytical and problem-solving abilities Excellent communication and storytelling with data Ability to work in a fast-paced, collaborative environment Education & Experience Bachelors/Masters/PhD in Computer Science, Statistics, Mathematics, or related field 6+ years of experience in data science, machine learning, or analytics roles Portfolio of projects (GitHub, Kaggle, research papers) is a plus Preferred Qualifications Experience with deep learning (CNN, RNN, Transformers) Knowledge of MLOps (model deployment, CI/CD pipelines) Familiarity with A/B testing and causal inference Background in NLP, LLMs (GPT, BERT), or generative AI

Artify Talent Studio 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

Roles and Responsibilities : Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions Proven ability to dive business results with their data-based insights Develop custom data models and algorithms to apply to data sets Use predictive modeling to increase and optimize customer experiences, revenue generation, targeting and other business outcomes Develop A/B testing framework and test model quality Coordinate with different functional teams to implement models and monitor outcomes Develop processes and tools to monitor and analyze model performance and data accuracy

Job Title: Senior Machine Learning Engineer Location: Pune, India Department: Enterprise Data & Analytics Advanced Analytics Team Employment Type: Full-time About the Role: We are looking for a Senior Machine Learning Engineer to join our Advanced Analytics IT Product Team. The team is responsible for developing cutting-edge data and analytics products that empower business functions to make smarter, data-driven decisions. This role is ideal for an experienced and proactive ML engineer who enjoys solving complex problems, building scalable solutions, and working with cross-functional teams in a dynamic global environment. Responsibilities: Design, build, test, deploy, and maintain machine learning and AI solutions across business domains. Collaborate with data scientists, engineers, and product teams to deliver reliable, production-grade ML pipelines. Develop data models, algorithms, and integrate them into enterprise-grade applications. Ensure solutions are secure, compliant, and follow industry best practices. Continuously improve ML products based on real-world performance metrics and feedback. Participate in code reviews, solution design, and incident resolution. Document technical designs and contribute to internal knowledge sharing. Lead ML engineering practices, mentor junior team members, and support agile development activities such as sprint planning and retrospectives. Qualifications: Education & Experience: Master's degree in Computer Science, Machine Learning, Statistics, Physics, Mathematics, or a related field. 4–6 years of hands-on experience in machine learning, data science, or data engineering. Technical Skills: Strong experience with AWS services: S3, DynamoDB, CloudFormation, CDK, Route53, AppFlow. AWS certifications are a plus. Hands-on experience with Databricks : PySpark, MLFlow, Unity Catalog, orchestration workflows. Databricks certifications preferred. Proficient in Python , SQL , and DBT . Familiar with tools like GitHub/GitLab , Airflow , and Terraform . Solid understanding of enterprise data (structured, unstructured, transactional, metadata) and integrations with systems like SAP ERP, Salesforce, and product data platforms. Strong foundation in CI/CD, testing practices, and production-grade software development. Experience with infrastructure-as-code, version control, and deployment automation. Knowledge of data privacy, cybersecurity, and regulatory compliance. Serve as the technical expert for ML engineering within the team. Drive architecture and design improvements for scalability and efficiency. Lead quality assurance activities, conduct code reviews, and ensure adherence to development standards. Guide and mentor junior engineers and contribute to capability building. Take on additional responsibilities such as Scrum Master or task force lead when needed. Agile working methodology with tools such as Jira, Confluence, and draw.io. Global, multi-cultural team focused on transparency, collaboration, and continuous learning. Encouraged to be self-organized, courageous, and solutions-oriented.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities • Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. • Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills • Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. For more information, visit www.genpact.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube! Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI.

Job Overview: We are seeking a talented and driven Machine Learning Engineer to design and optimize machine learning models that will enhance a variety of credit and operational processes. This role will involve building cutting-edge solutions in areas like underwriting, loan processing, fraud detection, and risk mitigation, while continuously driving improvements through innovation and advanced techniques. Key Responsibilities: - Model Development & Optimization: Design, deploy, and refine machine learning models to support key functions such as underwriting, account management, fraud detection, and loss prevention. - Advanced Techniques Implementation: Identify opportunities to implement advanced machine learning approaches-such as Natural Language Processing (NLP), Image Recognition, and Graph Mining-to address complex business challenges. - Collaboration & Knowledge Sharing: Work with internal and external resources, as well as open-source algorithms, to find the best solutions and improve model performance. - Risk Management Compliance: Partner with the Model Risk Management team to ensure models are developed with appropriate rigor and align with risk management and governance standards. - Cross-Functional Collaboration: Collaborate closely with Product and Engineering teams to ensure seamless model deployment and integration. - Performance Monitoring: Track the effectiveness of models through dashboards and key performance indicators (KPIs), ensuring continuous improvement. - Stakeholder Communication: Present model insights and performance reports to key stakeholders in Credit, Risk, and Business Units, making complex findings accessible and actionable. Qualifications: - Educational Background: Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. A Master's degree is highly preferred. - Experience: 6-12 years of hands-on experience developing and implementing machine learning models in a professional environment. - Technical Proficiency: Strong expertise in SQL and Python, with the ability to write efficient code for working with large datasets and creating advanced features. - Analytical Thinking: Exceptional attention to detail and an ability to uncover hidden data patterns through thorough investigation. - Machine Learning Expertise: Solid foundation in machine learning and statistical modeling, including supervised and unsupervised learning techniques like regression, decision trees, support vector machines, boosting, deep learning, and more. Must stay current with industry advancements to apply the best techniques. - Database Knowledge: Proficient in working with SQL, NoSQL, Hive, and other relevant database technologies. - Effective Communication: Strong ability to translate complex technical concepts into clear, understandable terms for non-technical stakeholders.

Role Data Scientist Primary Skill Python (DSA) Exploratory data analysis using pandas,numpy, Seaborn, Matplotlib TensorFlow, PyTorch, Scikit-learn Large-language models, RAG, MCP , Agentic AI Azure Cognitive services /Azure AI foundry Vertex- AI Secondary Skill Github Agile Problem solving skills System design thinking. Observability Experience 4 to 6 years

Responsibilities : The incumbent will lead a team of data scientists and campaign managers. S/He will work closely with cross functional teams like Subscriber Marketing, Content, Product, IT, Tech, and Customer Operations to identify & solve key business problems. Key responsibilities for this position are listed below: - Leverage Gen AI for Transformational initiatives at across various offerings - DTH, mobile app. - Building and improving Recommendation Engines, Propensity Modelling, Unsupervised Learning, Fraud Detection, Patterns & Visualisations - Improving the Quality, Performance and Effectiveness of the campaigns - Working on various statistical and data science models to test and evaluate them - Evaluating models and predict performance of data science models using ROC curve and Lift Analysis - Providing expertise to the organisation on statistical techniques - Building deep learning based complex systems utilising structured and unstructured data - Setting up and manage a team of data scientists and campaign managers - Collaborating with data engineering team on building data marts, reports, data warehouse, data pipelines and data tracking mechanisms - Micro segment the base for better upsell of content. Leverage AMS (Audience Measurement system). - Integrate data science models into various campaigns - Manage various segmented upselling and retention campaigns which will be administered through various modes of communication e.g. outbound, TV channels, SMS, emails, App Notifications, website etc The Person : - 10+ years in the Data Science and Analytics domain - Expertise in Predictive Analytics & Machine Learning concepts like such as regression, classification, SVM, recommendation engines, neural network etc. - Hands On experience to open source analytical tools - such as R, Python - Hands On experience of data visualization tools like Tableau - Experience of working on web analytics using tools like Mix Panel for analytics and experimentation - Exposure to implementing data science solutions in production environments - Exposure to Gen AI technology for solving business problems like NLU Search, CVM, Metadata enrichment etc. - Understanding of analytical architecture components; query languages, web services, APIs etc - Experience working on cloud and it's components: AWS / Azure / Google Cloud Platform (any one) - Experience working on Big Data technologies like Spark, PySpark, SparkR etc - Proven experience in Model to Market - Good understanding of commercial (revenue and retention) aspects of the business. - Experience of leading and driving multiple complex projects with a sharp customer-focus - Sound problem identification, judgment, resolution and decision-making skills - Innovation oriented and a proponent of disruptive and out-of-the-box thinking - High level of integrity, ownership and accountability - Excellent written and verbal communications; ability to articulate thoughts clearly and concisely; excellent interpersonal skills.

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

raja.a@honeybeetechsolutions.com resume share to • 4 to 10 years of hands-on experience in Data Science, Machine Learning, or Predictive Analytics. • Strong programming skills in Python and proficiency in deep learning frameworks and libraries such as TensorFlow, PyTorch, Pandas, and Scikit-Learn. • Strong expertise in Transformer Models, LSTM, and Time-Series Analysis. • Experience with Unsupervised Learning Techniques (DBSCAN, UMAP, KMeans).

Mandatory Skills: Technical Expertise in Forecasting & Machine Learning: Strong experience in Wind and Solar power forecasting with time series modelling techniques like ARIMA / SARIMA . Proficiency in machine learning models like Regression, XGBoost, Random Forest, and neural networks like LSTMs . Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras for time series forecasting. Domain Knowledge in Renewable Energy & SCADA: Hands-on experience working with SCADA data , weather forecast data , and NWP models . Understanding of weather forecasting methodologies and their impact on power generation predictions. Programming & Data Engineering: Strong Python programming skills, with expertise in libraries like pandas, NumPy, scikit-learn, TensorFlow, PyTorch, and Statsmodels. Proficiency in SQL, Data pipeline development , and Cloud platforms (Azure, AWS, or GCP). Experience in building scalable data architectures for production-ready machine learning models. Model Evaluation & Accuracy Metrics: Knowledge of forecasting accuracy metrics (RMSE, MAE, MAPE etc.) and best practices for model evaluation. Responsibilities: Exploratory Data Analysis (EDA) & Data Processing: Perform in-depth EDA to identify patterns, trends, and anomalies in SCADA and weather data. Develop feature engineering pipelines for time series forecasting, including lag features, rolling statistics, and weather variable transformations. Handle data cleaning, transformation, and augmentation techniques for improving forecasting accuracy. Renewable Energy Forecasting: Develop and optimize models for wind and solar power forecasting using time series analysis, machine learning, and deep learning techniques. Work with Numerical Weather Prediction (NWP) models and generate weather forecast data for improving forecasting accuracy. Understand and process SCADA data for predictive analytics and forecasting model improvements. Model Development & Evaluation: Implement time series forecasting models, including ARIMA, ARIMAX, SARIMA, LSTMs, XGBoost, Random Forest, and other regression-based techniques. Evaluate models using forecasting accuracy metrics such as RMSE, MAE, MAPE. Optimize model hyperparameters and validate results using appropriate cross-validation techniques. Data Engineering & Cloud Integration: Design and develop data pipelines for ingesting, processing, and storing renewable energy data efficiently. Work with SQL databases, Azure Data Factory, AWS S3, or other cloud data storage solutions . Optimize model deployment for real-time and batch processing in a cloud environment. Productization & Architecture: Develop scalable and efficient machine learning pipelines for operationalizing forecasting models. Work on cloud-based architectures (Azure, AWS, GCP) to support model deployment and integration into production systems. Collaborate with software engineers and DevOps teams for seamless model integration into forecasting products. Role & responsibilities

About the Role: Looking for a highly experienced Computer Vision Specialist / AI Engineer to join our dynamic team. The ideal candidate will have a proven track record of delivering real-world computer vision and deep learning solutions, particularly in smart monitoring and edge & cloud AI applications. This role demands deep technical expertise in designing and deploying vision-based solutions such as object detection, object tracking, facial recognition, behavioral analysis, ANPR and OCR. You will lead the development and deployment of scalable, production-grade AI systems. Lead the architecture, development, and deployment of computer vision systems from concept to production. Develop and optimize advanced vision algorithms and deep learning models for real-time performance. Optimize AI/ML models for deployment across edge, cloud, and hybrid environments using tools like TensorRT, TFLite, OpenVINO, and ONNX. Collaborate with hardware and software engineering teams to ensure system-wide performance optimization. Conduct thorough testing, benchmarking, and performance tuning of models and systems. Required Skills & Experience: 25 years of hands-on experience in Computer Vision, Deep Learning, and AI model deployment. Strong proficiency in Python , with production-level experience in writing clean, modular, and scalable code. Familiar with frameworks and tools such as OpenCV, TensorFlow, PyTorch, YOLO, MediaPipe, Dlib. In-depth knowledge of: Convolutional Neural Networks (CNNs) o Object detection and tracking o Facial recognition techniques o Video-based behavioral analysis RTSP streaming, CCTV camera systems, NVR/DVR integration Deployment experience on platforms including: Edge devices (NVIDIA Jetson, Raspberry Pi, Coral Edge TPU) o Cloud (AWS/Azure/GCP) with containerization tools (Docker) Strong understanding of MLOps tools and workflows, including model tracking, data versioning, monitoring, and retraining. Nice to Have: Familiar with LLM and Vision Language Models

About the Role: We are seeking a highly motivated and skilled Data Scientist with 25 years of industry experience in Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI (GenAI). The ideal candidate will have a strong foundation in Python programming and a passion for solving complex business problems using data. You will work on designing, developing, and deploying scalable AI solutions for real-world applications across domains. This is a hands-on role requiring technical expertise, experimentation, and collaboration across cross-functional teams. Key Responsibilities: Perform Exploratory Data Analysis (EDA) to uncover patterns, insights, and anomalies. Design, build, and optimize ML and DL models using Python for diverse business use cases. Develop and apply NLP techniques for text analysis and language understanding. Build, fine-tune, and deploy Generative AI solutions (LLMs, VLMs, RAG) tailored to enterprise needs. Create and maintain end-to-end ML pipelines , including data preprocessing, feature engineering, training, evaluation, and deployment. Manage and monitor models in production using MLOps workflows (CI/CD, model tracking, versioning, etc.). Stay updated with recent developments in AI/ML and continuously explore new tools and frameworks. Required Skills & Qualifications: Strong programming proficiency in Python is essential. Experience with Python libraries such as pandas, NumPy, scikit-learn, NLTK, Transformers (Hugging Face), TensorFlow/PyTorch . Solid understanding of machine learning algorithms, statistical modeling, and deep learning concepts. Hands-on experience in Natural Language Processing and Generative AI techniques (e.g., LLMs, RAG, VLMs, Agents). Experience with EDA, data preprocessing , and feature engineering. Familiarity with MLOps tools like MLflow, DVC or similar. Experience with Docker and containerized deployment of ML models. Working knowledge of databases both SQL and NoSQL . Experience deploying ML models in production environments . Familiarity with version control tools (e.g. Git) and collaborative workflows. Exposure to cloud platforms like AWS, GCP, or Azure is a plus.

Locations We are located in Austin (USA), Singapore, and Hyderabad (India). Job Locations: Hyderabad, Ahmedabad, Indore Role Overview We are looking for a highly skilled Senior Data Scientist with a passion for deploying and maintaining machine learning models, leading teams, and driving innovation. Summary: Years of Experience: Minimum of 8+ years Job Location: Hyderabad, Ahmedabad, Indore Notice Period: Immediate to 30 days Work Shift: General Shift What Youll Do Key Responsibilities: Lead the strategic direction of machine learning infrastructure with a focus on performance, scalability, and reliability. Drive innovation by developing advanced machine learning solutions. Collaborate with the Data Science team to deploy, maintain, and optimize ML models in production environments. Architect and oversee the development of real-time and batch inference systems. Mentor mid-level engineers, fostering growth and technical excellence. Conduct comprehensive code reviews and encourage a culture of continuous learning. Communicate insights and translate complex technical concepts into actionable business solutions. Stay ahead of industry trends, integrating new technologies and tools. Technical Skills Extensive experience with machine learning methodologies and infrastructure. Expertise in Python, TensorFlow, PyTorch, and other ML frameworks. Strong knowledge of real-time data processing and pipeline development. Proficiency in cloud platforms (AWS, GCP, Azure) for ML model deployment. Hands-on experience with Kubernetes, Docker, and container orchestration. Deep understanding of MLOps/DevOps best practices, including CI/CD pipelines, testing, and version control. Soft Skills Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Proven leadership experience, mentoring engineering teams to success. Ability to effectively translate technical concepts into actionable business solutions. Passion for continuous learning and staying updated with industry advancements. What Youll Bring Education: Bachelors or Masters degree in Computer Science, Data Science, or a related field. Proven experience in large-scale machine learning projects. Deep knowledge of deploying scalable, robust systems for real-time and batch inference use cases. Location: Jaipur

Dreaming big is in our DNA Its who we are as a company Its our culture Its our heritage And more than ever, its our future A future where were always looking forward Always serving up new ways to meet lifes moments A future where we keep dreaming bigger We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential The power we create together when we combine your strengths with ours is unstoppable Are you ready to join a team that dreams as big as you do AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology The teams are transforming Operations through Tech and Analytics, Do You Dream Big We Need You, Job Description Job Title: Data Scientist Location: Bangalore Reporting to: Senior Manager Analytics Purpose of the role Anheuser-Busch InBev (AB InBev)s Supply Analytics is responsible for building competitive differentiated solutions that enhance brewery efficiency through data-driven insights We optimize processes, reduce waste, and improve productivity by leveraging advanced analytics and AI-driven solutions, As a Data Scientist you will work at the intersection of Conceptualize the analytical solution for the business problem by implementing statistical models and programming techniques, Application of machine learning solutions, Best in class cloud technology & micro-services architecture, Use DevOps best practices that include model serving, data & code versioning, Key tasks & accountabilities Develop and fine-tune Gen AI models to solve business problems, leveraging LLMs, and other advanced AI techniques, Design, implement, and optimize AI-driven solutions that enhance automation, efficiency, and decision-making, Work with cloud-based architectures to deploy and scale AI models efficiently using best-in-class microservices, Apply DevOps and MLOps best practices for model serving, data and code versioning, and continuous integration/deployment, Collaborate with cross-functional teams (engineering, business, and product teams) to translate business needs into AI-driven solutions, Ensure model interpretability, reliability, and performance, continuously improving accuracy and reducing biases, Develop internal tools and utilities to enhance the productivity of the team and streamline workflows, Maintain best coding practices, including proper documentation, testing, logging, and performance monitoring, Stay up to date with the latest advancements in Gen AI, LLMs, and deep learning to incorporate innovative approaches into projects, Qualifications, Experience, Skills Level Of Educational Attainment Required Academic degree in, but not limited to, Bachelors or master's in computer application, Computer science, or any engineering discipline, Previous Work Experience Minimum 3 years of relevant experience, Technical Skills Required Programming Languages: Proficiency in Python, Mathematics and Statistics: Strong understanding of linear algebra, calculus, probability, and statistics, Machine Learning Algorithms: Knowledge of supervised, unsupervised, and reinforcement learning techniques, Natural Language Processing (NLP): Understanding of techniques such as tokenization, POS tagging, named entity recognition, and machine translation, LLMs: Experience with Langchain, inferring from LLMs and fine tuning LLMs for specific tasks, Prompt Engineering, Data Preprocessing: Skills in data cleaning, normalization, augmentation, and handling imbalanced datasets, Database Management: Experience with SQL and NoSQL databases like MongoDB and Redis, Cloud Platforms: Familiarity with Azure and Google Cloud Platform, DevOps: Knowledge of CI/CD pipelines, Docker, Kubernetes, Other Skills Required APIs: Experience with FastAPI or Flask, Software Development: Understanding of software development lifecycle (SDLC) and Agile methodologies, And above all of this, an undying love for beer! We dream big to create future with more cheers,

What we do : Our game-changing AI solutions revolutionize what people and businesses can achieve. Ara inference processors combined with our SDK deliver unrivaled deep learning performance at the edge to accelerate and optimize real-time decision making where every millisecond is critical, and power efficiency is a must. solutions embed high-performance AI into edge devices to create a smarter, safer, and more enjoyable world. Edge AI is on the brink of a boom, and looking forward to playing a significant role in it. This is what you are responsible for : - Will be part of a highly talented global team developing neural network systems. - Will have the opportunity to develop the application and system software for a cutting-edge AI silicon. - Member of a software engineering team, you will design and implement compilers, translators for AI computing system - Work closely with ASIC and hardware teams, propose architectural features and develop software for the system and build the highest perf/watt system Necessary Qualifications : - Excellent knowledge of Python/C/C++, data structures and algorithms. - Experience in neural network frameworks like TensorFlow, ONNX, Caffe, PyTorch etc. is a plus - BTech/MTech with 4+ years of experience in software development

Role & responsibilities Job Details: Role: Data Scientist Employment Type: FTE with Dimiour Work Location: Remote Shift Timings: UK Shifts Experience Required: 5+ Years Job Description: This individual contributor role will report to the Data Science Strategy Leader and will build our muscle around prescriptive analytics capabilities in commercial landscape. We are looking for individuals that have experience in one or more of the following focus areas: Strategic pricing optimization Revenue growth management Advanced marketing measurement and optimization Zero- and first-party consumer datasets Demand planning, forecasting and S&OP This role is ideal for candidates who excel at operating in environments with imperfect data, and comfortable prioritizing progress over perfection by making reasonable business assumptions. Responsibilities: Work with Data Science Strategy Leader to define data science use cases with a bias towards problems requiring prescriptive analytics, propose potential modeling approaches, assess feasibility, estimate effort and data requirements, draft project plans Build Proof-of-Concept data science models: acquire, cleanse, and harmonize data, analyze, and identify appropriate optimization algorithms, build models that are interpretable, explainable, and sustainable at scale and meets the business needs Engage stakeholders, including product and business teams, through frequent check-ins, progress updates, visualizations, and interactive dashboards designed for non-technical audiences Interpret model outputs, draw actionable insights, present findings, and make recommendations to cross-functional and senior leadership teams Collaborate with Enterprise AI/ML product teams and DTS Delivery teams to scale proven high value Proof-of-Concept models where enterprise certified products are required About You: Youre driven to perform at the highest level possible, and you appreciate a performance culture fueled by authentic caring. You want to be part of a company actively dedicated to sustainability, inclusion, wellbeing, and career development. To succeed in this role, you will need the following qualifications: Critical Technical Skills: 5+ years of experience with hands-on involvement in data science projects (research or consulting experience is a plus; experience in CPG/Retail, Digital Marketing, e-Commerce, or Revenue Management preferred) A bachelor’s degree in a quantitative field (e.g., Engineering, Computer Science, Statistics, Economics, or Mathematics) - An advanced degree in a quantitative field is preferred and will be accepted in lieu of 2 years of experience. Proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA – knowledge of optimization engines such as CPLEX or Gurobi is a plus) Proficiency in any data visualization software (e.g., Power BI, Tableau, Qlik, D3, Shiny) Theoretical or practical experience in mathematical optimization techniques ( e.g. linear and non-linear optimization, mixed integer programming, sensitivity analysis, constraint programming etc.) Experience in machine learning methods (e.g. multivariate regression, feature engineering, random forests, XGBoost, elastic nets, hierarchical Bayesian regression, unsupervised learning, clustering/segmentation) Preferred candidate profile

Key Responsibilities Provide strategic direction and technical leadership in applying machine learning/ AI within the organization, aligned with company goals and challenges. Influence R&D roadmap based on deep industry understanding and business needs. Drive innovation with novel solutions in the automotive industry, advancing applied science through latest research implementation. Act as a key liaison between R&D and stakeholders, ensuring technical alignment with business objectives. Collaborate with cross-functional teams to define and integrate machine learning solutions into products and services. Publish research in top conferences, advancing field knowledge. Provide mentorship to applied scientists, ensuring project success.Contribute to team growth through training and collaborative projects. Define metrics for model evaluation in offline and real-time settings. Quantify and communicate ML impact to executives, influencing decisions. Champion ethical AI practices, ensuring compliance and standards. Define best practices for ML model development, testing, validation, and monitoring. Demonstrate data-driven business acumen and technical expertise across development lifecycle. Maintain technical excellence in algorithm development and deployment. Required Qualifications Bachelors/ Masters / PhD in Data Science, Mathematics, Operations Research or related field. The right candidate has a background in probability and statistics, applied mathematics, or computational science and a history of solving difficult problems with good business impact using a scientific approach. Experience working with major ML algorithms and frameworks. Significant experience in Data Science and Machine Learning with a strong proven track record in delivering positive business impact. 11+ years of hands-on experience with analytics, data science and big data experience in a business context. Proficient in Machine Learning, Deep Learning and Explainable AI concepts with the ability to explain them clearly to non-technical audiences Experienced in developing and adapting state-of-the-art models for specific business needs, demonstrating a track record of success in complex, cross-functional projects. Utilizing Probability and Statistics to derive meaningful insights from data. Proficient in deep learning frameworks like TensorFlow, Keras, and PyTorch, and utilizing computer vision (OpenCV) and natural language processing (spaCy) libraries. Implementing deep learning techniques, particularly Neural Networks. Applying both fundamental and advanced Natural Language Processing concepts. Implementing Computer Vision methodologies. Experience with Large Language Models is a must. Should have fine-tuned LLM on domain dataset. Utilizing Git for efficient code management and version control. Leveraging cloud platforms such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services. Should be well versed with Design of Experiments. Experience in programming with Python and SQL or similar languages. Experience in distributed model training. Proficient in data visualization and presentation, transforming complex analyses into actionable insights. Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow). Experience using ML platforms such as Databricks and SageMaker. Preferred Qualifications Experience in Recommendation Engine, Natural Language Processing, Computer Vision Domain knowledge of automotive industry. Enjoys discovering and solving problems; proactively seeking clarification of requirements and direction; being a self-starter who takes responsibility when required. Familiarity with Spark Strong interpersonal, verbal, visual and presentation skills, ability to communicate complex findings in a simple manner to executives. Ability to work collaboratively across multiple products and application teams. A willingness to learn, share and improve.