4 Gradient Boosting Jobs

Job Description: We are seeking an experienced Data Scientist with expertise in advanced machine learning techniques to join our dynamic team. The ideal candidate will have hands-on experience developing and deploying models using ensemble methods and other cutting-edge ML algorithms, mostly in the US banking domain. Key Responsibilities: Develop and help deploy advanced machine learning models, including ensemble techniques, for customer lifecycle use cases (e.g., prescreen, acquisition, account management, collections, and fraud). Collaborate with cross-functional teams to define, develop, and improve predictive models that drive business decisions. Work with large datasets, utilizing tools like Python and SQL , to extract, clean, and transform data for modeling purposes. Ensure model robustness, interpretability, and scalability within banking environments. Strong problem-solving skills with the ability to handle complex datasets and turn them into actionable insights.

Dear Candidate, We are looking for a talented Data Scientist to analyze complex datasets, build predictive models, and extract valuable insights that drive business decisions. You will work with machine learning, statistical analysis, and big data technologies to develop scalable solutions. If you have a passion for data-driven decision-making and solving real-world problems, wed love to hear from you! Key Responsibilities: Collect, clean, and preprocess large datasets from multiple sources. Develop and deploy machine learning models for predictive analytics. Perform statistical analysis and hypothesis testing to drive business insights. Work with big data tools (Hadoop, Spark, or Databricks) to process large-scale datasets. Implement and optimize deep learning and AI algorithms where applicable. Collaborate with engineering teams to deploy models into production. Design and maintain data pipelines and ETL processes . Use data visualization tools (Tableau, Power BI, Matplotlib, Seaborn) to present findings. Ensure the scalability, accuracy, and performance of data models. Stay up to date with AI, ML, and data science trends to improve methodologies. Required Skills & Qualifications: Proficiency in Python or R for data analysis and machine learning. Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn). Strong knowledge of SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB). Hands-on experience with big data technologies (Spark, Hadoop, Databricks). Knowledge of cloud platforms (AWS, GCP, Azure) for data science workflows. Proficiency in data wrangling, feature engineering, and model optimization . Experience with A/B testing, hypothesis testing, and statistical modeling . Familiarity with MLOps, CI/CD for machine learning models . Strong problem-solving and analytical thinking skills. Excellent communication skills to translate data insights into business actions. Soft Skills: Strong problem-solving and analytical skills. Excellent communication skills to work with cross-functional teams. Ability to work independently and as part of a team. Detail-oriented with a focus on delivering high-quality solutions Note: If you are interested, please share your updated resume and suggest the best number & time to connect with you. If your resume is shortlisted, one of the HR from my team will contact you as soon as possible. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

Position Summary Continuing with the tradition of innovation, MetLife, as part of its Data and Analytics function, has established a Data and Analytics (DnA) center in India. The setup of DnA center is a key multi-year strategic initiative focused on scaling business solutions using AI, data science, data governance, data engineering, business intelligence, agile project management capabilities, enabling more cost-effective analytics operating model and increasing AI maturity across the MetLife global community. Role Value Proposition: We are looking for you: high performing data and analytics professional - driven by passion and purpose, to drive quality standards and support end-to-end development of actionable, high-impact AI solutions for MetLife enterprise functions and lines of businesses across markets. This position requires hands-on experience of developing an end-to-end Machine Learning/AI solution that can be leveraged for maximum business impact through on prem /cloud in both real time and batch mode depending upon business requirements. The role would collaborate with multiple stakeholders under the guidance of Lead/Director. Data scientists to develop robust, stable, and scalable advanced analytics/machine learning solutions leveraging new age methodologies/techniques. Superior problem-solving ability, curiosity, strong coding skills and attention to detail are the key success factors. Job Responsibilities a. Hands on development and implementation of AI/ generative AI models & algorithms to solve complex problems and drive innovation across organization. b. Collaborate with Lead Data Scientist/AI product owner to translate given business problem into analytical use-cases with defined outcomes. c. Perform data exploration, machine learning models development & active collaboration with cross functional teams d. Contribute to the implementation of AI solutions to deliver business impact with focus on value, success criteria alignment, scalability, and operationalization. e. Drive best practices throughout development process, efficient coding and publish learnings/feedback for continuous learning. f. Drive innovation within teams, by enhancing existing solutions and designing new ones. Knowledge, Skills, and Abilities Bachelor's/master's degree in an information technology/computer science or relevant domain Technology Skills > 4+ years of hands-on experience in Analytics, data science or similar function > Strong hands-on proficiency in any of Data Science technologies i.e., Python, PySpark, & have experience in machine learning libraries & frameworks such as Sklearn, TensorFlow, > Strong hands-on expertise in traditional as well as modern statistical & ML techniques like regression, support vector machines, Regularization, Boosting, Random Forests & other ensemble methods. > Good Understanding of NLP models using: Nltk, spacy, Word 2 Vec , BERT etc. Experience in technologies like Azure, AWS, and advanced analytics concepts like Simulation, Deep Learning etc. are considered as a plus. Experience > Ability to meet deadlines for product deliverables in a timely, proactive, and entrepreneurial manner. > General Management skills: > Analytical and problem-solving skills to ideate. > Excellent written and verbal communication skills; ability to discuss technical issues with peers, business stakeholders and senior management. > Strong conceptual and creative problem-solving skills; ability to learn new and complex concepts quickly.

Job Description Purpose of the role To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making Accountabilities Design analytics and modelling solutions to complex business problems using domain expertise. Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools. Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams. Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them. Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users. Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. Ensure all development activities are undertaken within the defined control environment. Analyst Expectations To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement. Requires in-depth technical knowledge and experience in their assigned area of expertise Thorough understanding of the underlying principles and concepts within the area of expertise They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate. Will have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for end results of a team’s operational processing and activities. Escalate breaches of policies / procedure appropriately. Take responsibility for embedding new policies/ procedures adopted due to risk mitigation. Advise and influence decision making within own area of expertise. Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct. Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function. Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Make evaluative judgements based on the analysis of factual information, paying attention to detail. Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents. Guide and persuade team members and communicate complex / sensitive information. Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. Additional Job Description Join us as a "Data Scientist" in Group Control Quantitative Analytics team at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. Group Control Quantitative Analytics (GC QA) is a global organization of highly specialized data scientists working on Machine Learning model development and model management including governance and monitoring. GC QA is led by Lee Gregory, who is Chief Data and Analytics Officer (CDAO) in Group Control. GC QA is responsible for developing and managing machine learning models (including governance and regular model monitoring ) and providing analytical support across different areas including Fraud, Financial Crime, Controls, Security etc. within Barclays. The Data Scientist" position provides project specific leadership in building targeting solutions that integrate effectively into existing systems and processes while delivering strong and consistent performance. Working with GC CDAO team, the Quantitative Analytics Data Scientist role provides expertise in project design, predictive model development, validation, monitoring, tracking and implementation. To be successful as a "Data Scientist" in Group Control Quantitative Analytics team, you should have experience with: Coding using Python. Machine Learning algorithms. SQL Distributed computing using Spark/PySpark. Predictive Model development. Model lifecycle and model management including monitoring. DevOps tools like Git/Bitbucket etc. Project management using JIRA. Some other highly valued skills may include: DevOps tools Teamcity, Jenkins etc. Knowledge in Fraud and Financial Crime domain. Knowledge of GenAI tools and working. DataBricks You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. Location: Noida.