6 Crossvalidation Jobs

Citi is seeking an energetic and motivated professional to join its Fraud Analytics team as a Specialized Analytics Sr. Analyst. In this role, you will be part of the Global Fraud Analytics team, responsible for developing and validating fraud models to support Citis North American Cards business. As a strategic professional, you will stay updated on the latest trends in the field and apply them to your work. Strong communication skills are essential for negotiating internally and collaborating with Strategy partners and Model Risk Management validators. Your responsibilities will include model development, validation, and testing of fraud detection models, ensuring compliance with regulatory requirements and industry best practices. You will work with large and complex data sets to evaluate business strategies, identify data sets using tools like Hive and SQL, and document data requirements. Specialization in fraud or risk domain is preferred. Additionally, you will assess risks when making business decisions, ensuring compliance with laws and regulations while safeguarding Citigroup, its clients, and assets. The ideal candidate will have 8+ years of hands-on analytical experience and 5+ years of experience in statistical analysis with proficiency in Python (Must), Hive, Spark, or SAS. Strong quantitative, analytical, and problem-solving skills are required, along with knowledge of statistical concepts, modelling techniques, and model evaluation techniques. You should also have strong communication and interpersonal skills, project management abilities, and the capacity to work independently. A Master's, Bachelor's, or PhD degree in Statistics, Economics, Finance, Mathematics, or a related quantitative field is required, with an Engineering or MBA background from a premier institute being an advantage. This is a full-time position in the Decision Management department, specifically in the Specialized Analytics (Data Science/Computational Statistics) job family at Citi. Citi is an equal opportunity and affirmative action employer, inviting all qualified and interested applicants to apply for career opportunities.,

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As a Senior Specialist in Software Development (Artificial Intelligence) at Accelya, you will lead the design, development, and implementation of AI and machine learning solutions to tackle complex business challenges. Your expertise in AI algorithms, model development, and software engineering best practices will be crucial in working with cross-functional teams to deliver intelligent systems that optimize business operations and decision-making. Your responsibilities will include designing and developing AI-driven applications and platforms using machine learning, deep learning, and NLP techniques. You will lead the implementation of advanced algorithms for supervised and unsupervised learning, reinforcement learning, and computer vision. Additionally, you will develop scalable AI models, integrate them into software applications, and build APIs and microservices for deployment in cloud environments or on-premise systems. Collaboration with data scientists and data engineers will be essential in gathering, preprocessing, and analyzing large datasets. You will also implement feature engineering techniques to enhance the accuracy and performance of machine learning models. Regular evaluation of AI models using performance metrics and fine-tuning them for optimal accuracy will be part of your role. Furthermore, you will collaborate with business stakeholders to identify AI adoption opportunities, provide technical leadership and mentorship to junior team members, and stay updated with the latest AI trends and research to introduce innovative techniques to the team. Ensuring ethical compliance, security, and continuous improvement of AI systems will also be key aspects of your role. You should hold a Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field, along with at least 5 years of experience in software development focusing on AI and machine learning. Proficiency in AI frameworks and libraries, programming languages such as Python, R, or Java, and cloud platforms for deploying AI models is required. Familiarity with Agile methodologies, data structures, and databases is essential. Preferred qualifications include a Master's or PhD in Artificial Intelligence or Machine Learning, experience with NLP techniques and computer vision technologies, and certifications in AI/ML or cloud platforms. Accelya is looking for individuals who are passionate about shaping the future of the air transport industry through innovative AI solutions. If you are ready to contribute your expertise and drive continuous improvement in AI systems, this role offers you the opportunity to make a significant impact in the industry.,

As a member of our team, you will be responsible for managing organizational strategy and operations through the design and statistical analysis of business initiatives and experiments. Your role will involve collaborating with business partners to understand and address their needs and issues effectively. Utilizing advanced knowledge of statistics and data mining techniques, such as predictive modeling and simulation, you will identify patterns and insights from business data. Additionally, you will be tasked with designing, developing, and evaluating statistical and predictive models to drive business solutions. In this position, you will act as the lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communication of findings and recommendations to management across various departments will be a crucial aspect of your role. Furthermore, you will support implementation efforts and lead and mentor the team working in the Data Competency Centre. To excel in this role, you should possess a Bachelor's degree in data science, computer science, electrical engineering, applied statistics, or physics with 8-10 years of relevant work experience in Data Science, Artificial Intelligence, or Machine Learning algorithm development. Alternatively, a Master's degree with 5+ years of relevant work experience or a PhD with 4+ years of relevant work experience in the aforementioned fields will also be considered. A working knowledge of budgets and financial statements is required. Key skills and competencies for this position include demonstrated experience in managing teams, coaching team members to drive results, proficiency in programming languages and statistical software tools (such as Python, SAS, R, JMP), relational databases (SQL server), and data analysis and visualization software (preferably PowerBI, SAS). You should also have experience with standard data science and machine learning packages, as well as machine learning model tradeoffs and computer vision models. Strong communication skills are essential to effectively collaborate with various business partners and communicate complex data relationships and statistical model results. Your essential responsibilities will involve statistical analysis and model development in collaboration with business partners, internal teams, and Enterprise Data Management. You will explore data using statistical techniques to answer business questions, build hypotheses, and identify research data attributes. Additionally, you will lead the development of experimental designs for business initiatives, apply advanced statistical techniques, build predictive models, and deploy computer vision models to meet business needs. Providing guidance and direction related to statistical analysis, as well as effectively communicating and delivering statistical and predictive model results to business partners, are critical aspects of this role. You will report to the Head of Automation Digital Transformation USA and will have direct reports. Some travel may be required for this position. This is a full-time role based in Plot No.A-1/1 SIPCOT Industrial Park, Sriperumbudur, Tamil Nadu, 602105, IN. If you believe you meet the qualifications and can excel in fulfilling the responsibilities outlined for this role, we encourage you to apply. All candidates receiving an offer of employment must successfully complete a background check and any other required tests. Job Identification: 1021960 Job Category: NPI-HSRT Integration Data Science Posting Date: 07/17/2025, 12:17 AM Job Schedule: Full time Work Schedule: Normal Shift New (PMT),

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

Key Responsibilities Extract and analyze data from company databases to drive the optimization and enhancement of product development and marketing strategies. Analyze large datasets to uncover trends, patterns, and insights that can influence business decisions. Leverage predictive and AI/ML modeling techniques to enhance and optimize customer experience, boost revenue generation, improve ad targeting, and more. Design, implement, and optimize machine learning models for a wide range of applications such as predictive analytics, natural language processing, recommendation systems, and more. Conduct experiments to fine-tune machine learning models and evaluate their performance using appropriate metrics. Deploy machine learning models into production environments, ensuring scalability Qualifications Bachelor's, Master's or Ph.D in Computer Science, Data Science, Mathematics, Statistics, or a related field. 2+ years of experience in Analytics, Machine learning, Deep learning. Proficiency in programming languages such as Python, and familiarity with machine learning libraries (e.g., Numpy, Pandas, TensorFlow, Keras, PyTorch, Scikit-learn). Strong experience with data wrangling, cleaning, and transforming raw data into structured, usable formats. Hands-on experience in developing, training, and deploying machine learning models for various applications (e.g., predictive analytics, recommendation systems, anomaly detection). In-depth understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning) and their appropriate use cases. Experience with model evaluation techniques (e.g., cross-validation, A/B testing, performance metrics). Experience with cloud platforms (AWS, GCP, Azure) for model deployment and scalal Proficiency in data processing and manipulation techniques. Excellent problem-solving skills and the ability to work effectively in a collabor environment. Strong communication skills to convey complex technical concepts to non-tech stakeholders. Good To Have Experience in the [banking/financial services/industry-specific] sector. Familiarity with cloud-based machine learning platforms such as Azure, AWS, or GCP. Skills: recommendation systems,pytorch,cloud,anomaly detection,numpy,python,data cleaning,deep learning,predictive analytics,a/b testing,machine learning,pandas,tensorflow,scikit-learn,data wrangling,cloud platforms (aws, gcp, azure),model evaluation techniques,cross-validation,keras,machine learning models,