1345 Data Scientist Jobs - Page 50

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

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

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

We are looking for an Associate Data Scientist to analyze and interpret complex datasets, applying advanced statistical and machine learning techniques to extract valuable insights and drive data-driven decision-making. You will work closely with cross-functional teams to identify business challenges and develop innovative solutions that optimize our products and services. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research. Key Responsibilities: Utilize advanced analytics techniques to analyze large and complex datasets, identifying patterns, trends, and correlations to uncover valuable insights. Develop and implement machine learning models and algorithms for predictive and prescriptive analytics. Clean, pre-process, and validate data to ensure accuracy, completeness, and consistency for analysis purposes. Apply knowledge of Large Language Models (LLMs) to enhance text analysis and generation tasks. Explore and evaluate state-of-the-art LLMs, adapt them to specific tasks, and fine-tune models as necessary to improve performance. Build and deploy scalable text analysis pipelines to process and analyze text data efficiently . Communicate complex findings and insights to both technical and non-technical stakeholders through effective data visualization and storytelling techniques. Propose solutions and strategies to business challenges . Collaborate with engineering and product development teams . The ideal candidate: Minimum 6 months of experience as a Data Scientist Experience in data analysis, and modeling. Solid understanding of statistical concepts and machine learning algorithms, with hands-on experience in applying them to real-world problems. Strong programming skills in languages such as Python or R Experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch Knowledge and hands-on experience with Large Language Models (LLMs), such as GPT-3 and BERT Familiarity with data visualization tools such as Tableau, Power BI, or Matplotlib to effectively communicate insights. B.E/B.Tech in Computer Science, Engineering or relevant field; OR graduate degree in Data Science or other quantitative field is preferred . Abilities and traits Analytical mind and business acumen Strong math skills (e.g. statistics, algebra) Problem-solving aptitude Excellent communication and presentation skills . What we offer: Competitive salary and benefits package. Opportunity to work with cutting-edge technologies. Flexible working hours and remote work options. Continuous learning and professional development opportunities. A collaborative and supportive work environment.

We are looking for a highly skilled and experienced Senior Data Scientist to join our team in Bengaluru. The ideal candidate will have 4-7 years of experience in data science, with a strong background in machine learning, deep learning, and natural language processing. ### Roles and Responsibility Develop and implement innovative AI solutions using Python and other programming languages. Collaborate with cross-functional teams to design and deploy scalable data pipelines. Conduct complex data analysis and provide actionable insights to stakeholders. Design and develop predictive models to drive business growth. Work closely with the Solution Architects on deploying AI POCs and scaling them up to production-level applications. Convert business problems into analytical problems and devise solution approaches. Clean, aggregate, analyze, and interpret data to derive business insights from it. Own the AI/ML implementation process: Model Design, Feature Planning, Testing, Production Setup, Monitoring, and release management. Extract data from complex PDF/Word Docs/Form entities, tables, and information comparison. ### Job Requirements Excellent academic background in data science, statistics, or a related field. Strong proficiency in Python and experience with deep learning frameworks such as TensorFlow or PyTorch. Experience with cloud-based platforms such as AWS or Azure is desirable. Strong understanding of statistical concepts and machine learning algorithms. Excellent communication and problem-solving skills. Ability to work in a fast-paced environment and meet deadlines. Solid background in Python with excellent coding skills. Minimum 4 years of core data science experience in one or more areas: Machine Learning (Regression, Classification, Decision Trees, Random Forests, Timeseries Forecasting and Clustering), Understanding and usage of Large Language Models like Open AI models like ChatGPT, GPT4, frameworks like LangChain and Llama Index, Deep Learning (DNN, RNN, LSTM, Encoder-Decoder Models), Natural Language Processing- Text Summarization, Aspect Mining, Question Answering, Text Classification, NER, Language Translation, NLG, Sentiment Analysis, Sentence Computer Vision- Image Classification, Object Detection, Tracking etc., SQL/NoSQL Databases and its manipulation components, Working knowledge of API Deployment (Flask/FastAPI/Azure Function Apps) and webapps creation, Docker, Kubernetes. Good understanding of open source LLM framework like Mistral, Llama, etc. and fine tuning on custom datasets. Knowledge of firm’s reporting tools and processes. Proactive, organized, and self-sufficient with ability to priorities and multitask. Analyses complex or unusual problems and can deliver insightful and pragmatic solutions. Ability to quickly and easily create/gather/analyze data from a variety of sources. A robust and resilient disposition able to encourage discipline in team behaviors.

We are looking for a highly skilled and experienced Senior Data Scientist with 3 to 8 years of experience to join our team in Bengaluru. The ideal candidate will have a strong background in applied mathematics, statistics, or data science, with excellent presentation and communication skills. ### Roles and Responsibility Support the Lead Data Scientist and team members in solving problems, analyzing data, and finding solutions. Lead the design, development, and deployment of advanced statistical methods, data science/ML, and other quantitative techniques to solve complex business problems. Collaborate with cross-functional teams to integrate data-driven insights into business strategies and operations. Oversee and drive the lifecycle of statistical and AI/ML decision support solutions and products, ensuring successful and timely delivery. Present data-driven insights and strategic recommendations to senior management and key stakeholders. Develop and maintain large-scale data systems, including data pipelines, architectures, and governance frameworks. ### Job Requirements Bachelor's degree in applied mathematics, statistics, applied mathematics, physics, economics, or other quantitative fields; a master's degree is preferred. Minimum 3 years of experience in Statistics, AI/Machine Learning/Data Science in technology companies, Life Sciences, Pharma, Biotech, or relevant regulated industries (banking, insurance, etc.). Solid understanding of applied statistical modeling, applied math modeling, and ML techniques, including clustering, classification, regression, dimensionality reduction, ensemble methods, and natural language processing. Proficiency in programming languages such as Python, PySpark, or R for data curation, transformation, analysis, modeling, and visualization tasks. Experience leading a team of Data Scientists, Data Analysts, or Data Engineers. Excellent presentation and communication skills, with the ability to communicate complex technical concepts to both technical and non-technical audiences.

We are looking for a highly skilled and experienced Senior Data Scientist with 3 to 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. ### Roles and Responsibility Contribute to the design and implementation of state-of-the-art AI solutions. Assist in developing and implementing AI models and systems using techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. ### Job Requirements Bachelor's or Master's degree in Computer Science, Engineering, or a related field; a Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements.

We are looking for a highly skilled and experienced Senior Data Scientist to join our team in Bengaluru. The ideal candidate will have 4 to 9 years of experience in data science, with a strong background in machine learning, deep learning, and natural language processing. ### Roles and Responsibility Develop and implement innovative AI solutions using Python and open-source models. Extract insights from complex PDF/Word Doc/Forms using techniques such as entity extraction, table extraction, and information comparison. Collaborate with Solution Architects on the deployment of AI POCs and scaling them up to production-level applications. Own the AI/ML implementation process, including model design, feature planning, testing, production setup, monitoring, and release management. Work closely with cross-functional teams to support global clients. Develop analytics-enabled solutions by integrating data science activities with business-relevant aspects. ### Job Requirements Excellent academic background in data science, Business Analytics, Statistics, Engineering, Operational Research, or other related fields. Solid background in Python with excellent coding skills. Minimum 4 years of core data science experience in areas such as machine learning, deep learning, and natural language processing. Good understanding of open-source LLM frameworks like Mistral, Llama, and fine-tuning on custom datasets. Experience with SQL/NoSQL Databases and API Deployment (Flask/FastAPI/Azure Function Apps). Strong written, oral, presentation, and facilitation skills. Ability to coordinate multiple projects and initiatives simultaneously through effective prioritization, organization, flexibility, and self-discipline. Demonstrated project management experience. Knowledge of firm’s reporting tools and processes. Proactive, organized, and self-sufficient with the ability to prioritize and multitask. Analyze complex or unusual problems and deliver insightful and pragmatic solutions. Ability to quickly and easily create/gather/analyze data from a variety of sources. A robust and resilient disposition able to encourage discipline in team behaviors.

Senior Data Scientist Experience: 5 - 7 Years Exp Salary : Upto INR 35 Lacs per annum Preferred Notice Period : Within 30 Days Shift : 10:00AM to 7:00PM IST Opportunity Type: Onsite (Bengaluru) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Azure Devops Or GitHub, Azure SQL DB or Cosmo DB, EKS, ETL, MLOps, supply chain, Machine Learning Good to have skills : CI/CD, Databricks, Demand Forecasting, Spark Aioneers (One of Uplers' Clients) is Looking for: Senior Data Scientist who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description As a Senior Data Scientist, you will be a pivotal member of the data science team within aioneers. You will be leading the solution implementation of data science work streams within our supply chain analytics projects. Often the projects involve solving complex supply chain problems like demand forecasting, multi-echelon inventory optimization, production scheduling, intelligent order fulfillment, rough cut capacity planning (RCCP) etc. You will also provide technical guidance and mentorship junior data scientists in the team. You will own development and implementation of end-to-end life cycle of machine learning solutions from data modelling, feature engineering, ML solution structuring to MLOps process implementation of automated model serving You will play the role of a technology architect to design efficient MLOps process for large scale model deployments and high frequency servings using Azure data and ML services You will provide thought leadership to solution architects and project managers to come up with effective solution architecture for clients problems You will be building heuristics, Operations research techniques based (like linear programming and discrete optimization) solutions to solve optimization problems in supply chain space You will also lead the data engineering work activities within the projects to create required data models with features stores for ML implementations and post processing activities to make the outputs consumable for business use cases YOUR PROFILE We are looking for someone with 5+ years of relevant data science and machine learning experience in solving supply chain problems Data Science And Machine Learning Skills Understanding of statistical methods (e.g., regression, hypothesis testing) and optimization techniques like linear programming and mixed-integer programming for supply chain problems Proficiency in methods like ARIMA, SARIMAX, Prophet, or advanced techniques using neural networks (e.g., LSTMs, Temporal Fusion Transformer) Familiarity with supervised and unsupervised learning for classification (e.g., demand segmentation) and clustering (e.g., supplier categorization) Knowledge of CI/CD pipelines for ML, including retraining, deployment, and monitoring models using Azure DevOps or GitHub Actions Supply Chain Domain Knowledge: Seasoned expertise in demand forecasting using ML. Understanding the nuances of intermittent, erratic and lumpy demand patterns and how to solve them using ML techniques Knowledge of EOQ, reorder point models, safety stock modelling and inventory simulation techniques would be a plus Programming and Technical Skills Expertise in setting up end to end MLOps processes - model training, deployment, and tracking experiments Expertise in creating data pipelines for ETL processes and connecting supply chain data sources Proficiency in integrating ERP data from systems like SAP into Azure via connectors or APIs Deploying scalable ML models as APIs using AKS (Kubernetes) Expertise in handling large-scale supply chain datasets using Spark, Databricks, or Azure Synapse Advanced query skills in Azure SQL Database or Cosmos DB for real-time analytics Advanced proficiency in Python for ML modelling, data analysis, and libraries like Scikit-learn, PyTorch, TensorFlow Version control and automating deployments using Azure DevOps or GitHub Actions Ability to think through automation, pipeline design and other MLOps processes Conceptual and pragmatic knowledge of the concepts of data modelling, feature engineering, fine tuning machine learning models, statistical model validation Educational Background and Experience Engineering degree in computer science, informatics, data analytics and other relevant branches Affinity for new technologies and a drive for independent learning Affinity for an open feedback culture with flat hierarchies WHY AIONEERS? At aioneers, we are building the next generation innovative solutions on supply chain technologies. What we can offer is a wonderful team culture, flexible work hours, respect for your ideas, open discussions / open door policies and attractive remuneration. Your results count and not the hours. You will have the chance to actively participate in the development and execution of innovative business strategies on an international scale. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: aioneers is a software and consulting company headquartered in Mannheim, Germany. We help businesses optimize their supply chain using our best-in-class supply chain expertise and our AI-powered technology, the AIO Platform. About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Domain: Retail Banking / Credit Cards Location: Mumbai/ Bengaluru Experience: 3-5 years Industry: Banking / Financial Services (Mandatory) Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us. What do we expect from you? Build and validate credit risk models , including application scorecards and behavior scorecards (B-score), aligned with business and regulatory requirements. Use advanced machine learning algorithms such as Logistic Regression, XGBoost , and Clustering to develop interpretable and high-performance models. Translate business problems into data-driven solutions using robust statistical and analytical methods. Collaborate with cross-functional teams including credit policy, risk strategy, and data engineering to ensure effective model implementation and monitoring. Maintain clear, audit-ready documentation for all models and comply with internal model governance standards. Track and monitor model performance, proactively suggesting recalibrations or enhancements as needed. What do you need to excel at? Writing efficient and scalable code in Python, SQL, and PySpark for data processing, feature engineering, and model training. Working with large-scale structured and unstructured data in a fast-paced, banking or fintech environment. Deploying and managing models using MLFlow, with a strong understanding of version control and model lifecycle management. Understanding retail banking products , especially credit card portfolios , customer behavior, and risk segmentation. Communicating complex technical outcomes clearly to non-technical stakeholders and senior management. Applying a structured problem-solving approach and delivering insights that drive business value. What are we looking for? Bachelors or masters degree in Statistics, Mathematics, Computer Science , or a related quantitative field. 35 years of experience in credit risk modelling , preferably in retail banking or credit cards. Hands-on expertise in Python, SQL, PySpark , and experience with MLFlow or equivalent MLOps tools. Deep understanding of machine learning techniques including Logistic Regression, XGBoost, and Clustering. Proven experience in developing Application Scorecards and behavior Scorecards using real-world banking data. Strong documentation and compliance orientation, with an ability to work within regulatory frameworks. Curiosity, accountability, and a passion for solving real-world problems using data. Cloud Knowledge, JIRA, GitHub(good to have)

Key Responsibilities Causal Inference & Experimentation Design and analyze experiments (A/B tests, observational studies) to identify causal relationships between variables. Apply advanced causal inference methods (e.g., propensity score matching, difference-in-differences, instrumental variables, DAGs) to estimate treatment effects. Use tools like DoWhy , CausalML , or EconML to model causal relationships. Forecasting & Multivariate Analysis Develop time-series forecasting models (e.g., ARIMA, Prophet, LSTM) to predict business metrics (sales, demand, churn). Perform multivariate regression analysis to identify key drivers of outcomes. Validate model accuracy and refine approaches based on feedback. Data Analysis & Visualization Clean, preprocess, and analyze large datasets to extract meaningful patterns. Build dashboards and reports to communicate findings to stakeholders using tools like Tableau, Power BI, or Python (Matplotlib/Seaborn). Collaboration Partner with product, marketing, and operations teams to define KPIs and design data-driven strategies. Translate complex technical results into actionable business recommendations. Technical Skills : Causal Inference : Proficiency in methods like propensity score matching, synthetic controls, and counterfactual analysis. Forecasting : Experience with time-series models (Prophet, ARIMA) and machine learning frameworks (Scikit-learn, TensorFlow). Programming : Strong Python/R skills (Pandas, NumPy, StatsModels, CausalInference). Data Wrangling : SQL proficiency for querying large datasets. Experience : 5+ years in data science, with a focus on causal inference and experimental design. Experience in industries like e-commerce, retail, or tech is a plus.

Walk-In Drive for Machine Learning / Deep Learning Engineers Date : Saturday, 17th May Time : 9:30 AM to 1:30 PM Location : Mirafra Technologies, Akshay Tech Park, Plot No. 72 & 73, 2nd Floor, EPIP Zone, Whitefield, Bengaluru, Karnataka 560066 Experience : 5 to 10 Years Are you an experienced ML/DL Engineer ready to work on impactful real-world applications? Were hiring skilled professionals with expertise in Machine Learning / Deep Learning , especially those with experience in the HVAC domain . Who Should Attend? We are looking for professionals with: 5 to 10 years of experience in Machine Learning / Deep Learning Strong coding and modeling experience in Python Hands-on knowledge of TensorFlow, PyTorch, Keras , Scikit-learn, etc. Experience in NLP, Computer Vision, or Predictive Maintenance HVAC domain knowledge or exposure to building automation, control systems, or energy optimization is a strong advantage Experience with deploying ML models on cloud platforms (AWS/GCP/Azure) preferred Key Responsibilities Develop and deploy ML/DL models in areas like predictive maintenance, energy analytics , and smart building solutions Work with cross-functional teams to deliver intelligent HVAC solutions Perform data preprocessing, feature engineering, model training, and evaluation Ensure high-performance and scalable model deployments in production environments What to Bring Updated Resume Government ID Proof Recent Passport Size Photograph Note HVAC domain experience is preferred but not mandatory.

In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? 5+ years of experience with developing solutionsusing machine learning, operation research and pattern searching methods onlarge scale data. B.E/B.Tech/MSin Machine Learning, Computer Science,Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models likehierarchical models, stochastic models, time series, survival and econometricmodels Expert in at least one of the deep learningframeworks such as PyTorch, MxNet, or Tensorflow Hands-on experience in using Spark (Scalaor Pyspark) to process data at large scale and database schemadesign for ML pipelines a must Contribution to open-source ML packages/researchpublications will be a huge bonus Can yousay Yes, I will! to the following? 5+ years of experience with developing solutionsusing machine learning, operation research and pattern searching methods on largescale data. Good understanding on statistical models likehierarchical models, stochastic models, time series, survival and econometricmodels Expert in at least one of the deep learningframeworks such as PyTorch, MxNet, Tensorflow. Hands-on experience in using Spark (Scalaor Pyspark) to process data at large scale and database schemadesign for ML pipelines a must Contribution to open-source ML packages/researchpublications will be a huge bonus

Job overview: In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? experience with developing solutions using machine learning, operation research and pattern searching methods on large scale data. B.E/B.Tech/MS in Machine Learning, Computer Science, Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models like hierarchical models, stochastic models, time series, survival and econometric models Expert in at least one of the deep learning frameworks such as PyTorch, MxNet, or Tensor flow Hands-on experience in using Spark (Scala or Py spark) to process data at large scale and database schema design for ML pipelines a must Contribution to open-source ML packages/research publications will be a huge bonus

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence Interview Process The application process will include testing technical proficiency, case study, and team-fit interviews. Please include a brief note introducing yourself, what youre looking for when applying for the role, and your potential value-add to our team.

Roles and Responsibilities : Mine, process, and analyze hit/event level web, product, sales, and digital marketing data. Develop predictive scoring models and apply machine learning algorithms to customer profile, journey, and usage data. Deploy ML models into production data sets that can be leveraged for testing/activation on our websites, product applications, and sales/marketing channels. Develop ML model activation testing plans, benchmarking, and measure final outcomes. Enhance/Build data visualizations and reports in Tableau. Work with data engineers to improve and maintain the customer360 data model by defining new feature requirements, making improvements to taxonomy, and identifying bug fixes. Work with cross-functional teams (BI Enterprise Data Warehouse, Salesforce MOPS, IT, Product teams) to improve data quality in the customer360 data model. Develop a good understanding of the business's model, objectives, issues, and challenges by interacting and collaborating with leaders and stakeholders. Document all model methodology, outcomes, and activated performance. Desired Candidate Profile : Experience using Python, SciKit, SQL, Snowflake, hit-level Adobe Analytics data, product usage data, Jupyter Notebooks, Amazon SageMaker, Airflow, Github. Proficiency with data mining, mathematics, and statistical analysis techniques. Experience with predictive modeling techniques, unsupervised, supervised, reinforcement, causal inference machine learning techniques. Experience with the following ML steps: data prep, choosing model, feature creation and selection, training, evaluation, parameter tuning, making predictions. Experience with cookie-level advertising platform data (Google, Bing, Epsilon, LinkedIn, Facebook etc.) and measuring demand generation KPIs (ROAS, CTRs, Impressions, MTA Attribution). Experience with cookie-level web/product data and KPIs like usage, conversion funnels, bounce rates, unique visitors, sessions, hits/events, pathing and journey optimization. Experience with designing A/B/Multivariate/Lift testing and measurement for activated ML models in both digital and offline demand generation channels. Experience gathering and refining requirements from business stakeholders. Experience communicating ML methodology and findings to both technical and non-technical audiences. Preferred: previous experience in an engineering role building, testing, deploying, and measuring ML models using an ensemble approach. Perks and Benefits : 5 Days Working. Performance Linked Incentives. Scholar Policy.

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

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Summary: As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, and GenAI models. Your role involves creating cloud or on-prem application pipelines with production-ready quality, incorporating deep learning, neural networks, chatbots, and image processing. Location: Pan India

Amex GBT is a place where colleagues find inspiration in travel as a force for good and - through their work - can make an impact on our industry. We re here to help our colleagues achieve success and offer an inclusive and collaborative culture where your voice is valued. The associate data scientist will be a member of the data analytics team and will support building big data, data science, data quality, and BI/MI/AI solutions. What Youll Do: An ideal candidate will have a growth-oriented, lean-startup approach for building hands-on data science solutions. The ideal candidate will propose, experiment, implement, and operationalize advanced predictive, preemptive data solutions designed to help traveler, travel-manager, supplier, and client outcomes. The role will span full-scale product, enterprise, and operational data science. What Were Looking For: The candidate will focus and thrive in a hands-on applied role. Knowledge of AI, machine learning, and data science techniques are required. Expertise in python programming is critical. Location India The #TeamGBT Experience Work and life: Find your happy medium at Amex GBT. Flexible benefits are tailored to each country and start the day you do. These include health and welfare insurance plans, retirement programs, parental leave, adoption assistance, and wellbeing resources to support you and your immediate family . Travel perks: get a choice of deals each week from major travel providers on everything from flights to hotels to cruises and car rentals. Develop the skills you want when the time is right for you, with access to over 20,000 courses on our learning platform, leadership courses, and new job openings available to internal candidates first. We strive to champion Inclusion in every aspect of our business at Amex GBT. You can connect with colleagues through our global INclusion Groups, centered around common identities or initiatives, to discuss challenges, obstacles, achievements, and drive company awareness and action. And much more! A ll applicants will receive equal consideration for employment without regard to age, sex, gender (and characteristics related to sex and gender), pregnancy (and related medical conditions), race, color, citizenship, religion, disability, or any other class or characteristic protected by law. Click Here for Additional Disclosures in Accordance with the LA County Fair Chance Ordinance. Furthermore, we are committed to providing reasonable accommodation to qualified individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the hiring process. For details regarding how we protect your data, please consult the Amex GBT Recruitment Privacy Statement .

locationsBangalore,India time typeFull time posted onPosted 30+ Days Ago job requisition idR0000387027 About us: As a Fortune 50 company with more than 450,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. About Target Tech: Every time a guest enters a Target store or browses Target.com nor the app, they experience the impact of Targets investments in technology and innovation. Were the technologists behind one of the most loved retail brands, delivering joy to millions of our guests, team members, and communities. Join our global in-house technology team of more than 5,000 of engineers, data scientists, architects and product managers striving to make Target the most convenient, safe and joyful place to shop. We use agile practices and leverage open-source software to adapt and build best-in-class technology for our team members and guestsand we do so with a focus on diversity and inclusion, experimentation and continuous learning About Team A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Position overview: Develop and deploy scalable deep learning models to improve experience of Target guest Architect and implement large-scale AI systems using test-driven development practices Build NLP technology for query and document analysis, processing, and understandig Create data pipelines for feature/label extraction and generation Conduct data analysis to identify opportunities and improve models Conduct research to advance the state-of-the-art machine learning and NLP technologies Contributing to the operations/building of AI pipelines Adopting Target's infrastructural platforms and operationalize tools and systems around them Mentor and partner with other engineers to develop software that meets business needs Follow agile methodology for software development and technical documentation Innovate constantly and keep systems up to date with current technologies About you: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience 6+ years of experience in end-to-end application development, data exploration, data pipelining, API design, optimization of model latency 2 plus years of experience deploying Machine Learning algorithms into production environments - including model and system monitoring and troubleshooting Highly proficient programming in Java/ Scala and/ or Python Good understanding of Big Data tech - specifically Hadoop, Kafka, Spark Solid understanding of data analysis techniques, including data cleaning, preprocessing, and visualization Demonstrated ability collaborating with data scientists, software engineers and product managers to understand the business requirements and translate to machine learning solutions at scale Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives Self-driven and results oriented - able to meet tight timelines Know More About Us Here: Life at Target- Benefits- Follow us on social media Target Tech- https://tech.target.com/

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

Assar Vehicle Rental Services Private Limited 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

Job Title: Data Scientist Location: Hyderabad Experience: 5-8 Years Required Skills: ML, DL, Python, TensorFlow, PyTorch, Keras, SQL Job Description: Design, develop, and deploy machine learning (ML) and deep learning (DL) models to address complex business challenges. Utilize Azure and other cloud-based platforms to build, scale, and optimize ML/DL solutions. Collaborate with cross-functional teams to gather business requirements and deliver data-driven insights. Communicate complex technical concepts effectively to non-technical stakeholders. Write high-quality, production-ready Python code using frameworks such as TensorFlow, PyTorch, and Keras. Knowledge of writing complex SQL. Demonstrate a strong understanding of machine learning algorithms, statistical modeling techniques, and Generative AI frameworks (e.g., GPT, GANs). Have experience with large language models (LLMs) and retrieval-augmented generation (RAG) models. Explore and implement Generative AI techniques, including natural language processing (NLP) and image generation, to create innovative solutions. Hold a Master s degree in Computer Science, Engineering, Statistics, or a related field. Possess extensive experience in deep learning and machine learning methodologies. Exhibit excellent knowledge of Python programming and data analysis tools. Demonstrate strong problem-solving and analytical skills. Stay current with the latest advancements in ML/DL and evaluate new technologies for potential adoption. Exhibit excellent communication and interpersonal skills for effective collaboration in a team environment.

- Python, R, or Java - machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) - Tableau, Power BI, Matplotlib, Seaborn - big data technologies (e.g., Hadoop, Spark) & cloud platforms (e.g., AWS, Azure, GCP) - SQL and NoSQL databases