Developing innovative data products and implementing automation, advanced AI/ML, and Generative AI capabilities to drive business value through demand forecasting and analytics.
Responsibilities
Develop and maintain high-accuracy short-term and long-term demand forecasts at Automotive Segmentation and Powertrain levels.
Build, validate, and deploy time-series models (e.g. ARIMA) and ML algorithms to identify market trends.
Proactively integrate Generative AI / Agentic AI and other modern AI tools into daily workflows.
Act as a strategic partner to Sales, Marketing and Finance teams, translating analytical outputs into clear business recommendations.
Lead monthly forecasting reviews, presenting findings to senior stakeholders.
Lead data science initiatives to drive business value for Visa’s Japan market
Responsibilities
Drive value from Visa’s data assets
Deliver data science projects
Draw fact-based insights and make actionable recommendations
Build complex statistical models
Provide data visualization
Requirements
Post graduate degree in Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics or engineering, or equivalent experience
M2 internship aims to develop a machine-learning analysis framework to understand the driving mechanisms controlling atmospheric NH3 concentrations in north-west Europe using a combination of in-situ ground-level and satellite data.
Compensation
Research internship – 6 months
Responsibilities
Literature review: Investigate existing statistical modelling and machine-learning methods
Exploratory data analysis: Characterize available datasets
Methodological development: Process and implement the modelling framework, select relevant features, implement and optimize machine-learning models
Interpretation and visualization: map results, policy implications
Lead analytics engagements to evaluate client behaviours and optimize business decisions related to product, campaigns, pricing, and other business areas for the Credit Cards portfolio.
Responsibilities
Lead analytics engagements for Credit Cards portfolio
Integrate domain knowledge with analytical capabilities to deliver value to stakeholders
Identify and leverage statistical techniques to extract actionable insights
Apply advanced machine learning algorithms and AI-driven methodologies
Build data pipelines and visualizations from multiple data sources
Requirements
Degree in a quantitative field such as mathematics, statistics, computer science, economics, engineering, physics, or business
Advanced degree such as MMA, MBAN, MSc, MA, or MBA
Nice to have: Digital analytics experience (Adobe)
Mistral AI is seeking Applied Scientists and Research Engineers focused on tabular data. You will design, train, and deploy SOTA models that understand, query, and reason over structured data, and apply them to diverse use cases.
Responsibilities
Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs.
Generate and curate datasets of tables, spreadsheets and databases, and build evaluators and benchmarks for table understanding, text-to-SQL, and prediction on tabular data.
Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.
Collaborate with cross-functional teams to tackle complex use cases.
Manage research projects and communications with client research teams.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Focuses on traditional machine learning techniques like regression, classification, and statistical modeling.
Locations (4)
Chennai, Tamil Nadu, India
Coimbatore, Tamil Nadu, India
Hyderabad, Telangana, India
Bangalore, Karnataka, India
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
The starting pay range for this role is $70/Hr to $80/Hr.
Responsibilities
Partner with an assigned CIO organization as a primary AI/ML engineering lead, converting business problems into measurable machine learning and generative AI use cases.
Design, develop, test, deploy, and support production-grade solutions spanning predictive machine learning, deep learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI.
Prepare and analyze structured and unstructured data using Python, NumPy, Pandas, Matplotlib, and Seaborn; perform data quality analysis, preprocessing, feature engineering, and exploratory analysis.
Develop supervised and unsupervised learning solutions using techniques such as linear and logistic regression, decision trees, random forests, gradient boosting/XGBoost, support vector machines, K-Means, DBSCAN, PCA, and other dimensionality-reduction methods.
Build deep learning solutions with PyTorch (preferred) or TensorFlow/Keras, applying neural networks, CNNs, RNNs/LSTMs, transformers, attention mechanisms, and transfer learning where appropriate.
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related field, or equivalent practical experience.
Internship offer: Spatial drivers of atmospheric NH3 in north-west Europe based on long-term observationsInstitut Mines-Télécom · Douai, France
Sr Data ScientistNextEra Energy · Juno Beach, US
Applied Scientist - Research Engineer (Tabular Data), EMEAMistral · Paris, France