411 Logistic Regression Jobs - Page 15

About the Role The Data Science department plays a pivotal role in our company, generating value to client by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making. What Youll Be Doing Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the companys analytical capabilities Qualifications B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field 3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production. Strong understanding and practical experience with various machine learning algorithms. Proficiency in Python, Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions Proficiency in data visualization libraries, to create meaningful visual representations of complex data Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment Advantages: Experience in the fraud domain Experience with Airflow, CircleCI, PySpark, Docker and K8S Senior Data Scientist About the Role The Data Science department plays a pivotal role in our company, generating value to client by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making. What Youll Be Doing Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the companys analytical capabilities Qualifications B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field 5+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production. Strong understanding and practical experience with various machine learning algorithms. Proficiency in Python, Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions Proficiency in data visualization libraries, to create meaningful visual representations of complex data Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment Advantages: Experience in the fraud domain Experience with Airflow, CircleCI, PySpark, Docker and K8S Data Scientist- Autonomous About Us Empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world s biggest brands and publicly traded companies selling online rely on us for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. We are proud to work with incredible companies in virtually all industries including Wayfair, Acer, Gucci, Lorna Jane, GoPro, and many more We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose every day. About the Role The Research and Data Science department plays a pivotal role in our company, generating value to client by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making. What Youll Be Doing Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the companys analytical capabilities Qualifications B.Sc (M.Sc is a plus) in Statistics, Computer Science, Mathematics, or a related field 3+ years of proven experience designing and implementing machine learning algorithms and techniques in production grade Strong understanding and practical experience with various machine learning algorithms, such as linear regression, logistic regression, decision trees, similarity search, neural networks, and deep learning Proficiency in programming languages such as Python or R for data manipulation, statistical analysis, and machine learning model development Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions Proficient in data visualization libraries (e.g., Matplotlib, Seaborn, ggplot) to create meaningful visual representations of complex data Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environmentAdvantages: Experience in the fraud domain Experience with Airflow, CircleCI, PySpark, Docker and K8S EXPERIENCE 6-8 Years SKILLS Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): AI/ML Development, Data Science

Senior analyst with good ML model experience for the Regions Bank account Job Description: Primary Responsibilities for a Risk Data Scientist on the BSA/AML/OFAC Model Development and Monitoring Team: Design and develop transaction monitoring scenarios. Improves segmentation for the scenarios/models using techniques such as clustering. Executes periodic tuning for the threshold parameters of the scenarios through sample collection. Develops post processing models to reduce the number of false positives generated by the scenarios using techniques such as rare event logistic regression and machine learning algorithms. Researches and develops algorithms that incorporates fuzzy logic for OFAC sanction screening and other types of screening processes. Develops post processing models that incorporate Natural Language Processing techniques to reduce the number of false positives. Implementation of models. Develops and executes ongoing monitoring plan to monitor the performance of the models. Documentation of the model development, especially the implementation process. Supports model validation activities. Ad hoc analysis to address requests from business partners. Requirements Bachelor s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, AND six (6) years related experience. Master s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, AND four (4) years related experience. OR PhD degree in Statistics, Operations Research, Industrial Engineering, Mathematics, or Physics, AND two (2) years related experience. Skills and Competencies High proficiency with Python, R, SAS, and SQL. Advanced data sourcing and management skills. Enhanced experience with web scraping. Knowledge and experience with CDSW platform. Experience with software development, especially deployment. Experience with classification models. Location: DGS India - Bengaluru - Manyata N1 Block Brand: Merkle Time Type: Full time Contract Type: Permanent

Strong experience in Python 2+ years experience of working on feature/data pipelines using PySpark Understanding and experience around data science Exposure to AWS cloud services such as Sagemaker, Bedrock, Kendra etc. Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practice Experience with statistical models e.g., multinomial logistic regression Experience of technical architecture, design, deployment, and operational level knowledge Exploratory Data Analysis Knowledge around Model building, Hyperparameter tuning and Model performance metrics. Statistics Knowledge (Probability Distributions, Hypothesis Testing) Time series modelling, Forecasting, Image/Video Analytics, and Natural Language Processing (NLP). Good To Have: Experience researching and applying large language and Generative AI models. Experience with LangChain, LLAMAIndex, Foundation model tuning, Data Augmentation, and Performance Evaluation frameworks Able to provide analytical expertise in the process of model development, refining, and implementation in a variety of analytics problems. Knowledge on Docker and Kubernetes. Generate actionable insights for business improvements. Ability to understand business requirements. Write clean, efficient, and reusable code following best practices. Troubleshoot and debug applications to ensure optimal performance. Write unit test cases Collaborate with cross-functional teams to define and deliver new features Use case derivation and solution creation from structured/unstructured data. Actively drive a culture of knowledge-building and sharing within the team Experience applying theoretical models in an applied environment. MLOps, Data Pipeline, Data engineering Statistics Knowledge (Probability Distributions, Hypothesis Testing)

Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : PySpark Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Developer, you will design, build, and configure applications to meet business process and application requirements. You will be responsible for developing and implementing software solutions using PySpark. Your typical day will involve collaborating with the team to understand business needs, designing and coding applications, and ensuring the applications meet quality standards and performance requirements. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Design, build, and configure applications to meet business process and application requirements.- Collaborate with the team to understand business needs and translate them into technical requirements.- Develop and implement software solutions using PySpark.- Ensure the applications meet quality standards and performance requirements.- Troubleshoot and debug applications to resolve issues and optimize performance. Professional & Technical Skills: - Must To Have Skills: Proficiency in PySpark.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 2 years of experience in PySpark.- This position is based at our Hyderabad office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Service Management Lead Project Role Description : Lead the delivery of programs, projects or managed services. Coordinate projects through contract management and shared service coordination. Develop and maintain relationships with key stakeholders and sponsors to ensure high levels of commitment and enable strategic agenda Must have skills : ServiceNow Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Service Management Lead, you will lead the delivery of programs, projects, or managed services. Coordinate projects through contract management and shared service coordination. Develop and maintain relationships with key stakeholders and sponsors to ensure high levels of commitment and enable strategic agenda. Roles & 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.- Lead the delivery of programs, projects, or managed services.- Coordinate projects through contract management and shared service coordination.- Develop and maintain relationships with key stakeholders and sponsors to ensure high levels of commitment and enable strategic agenda. Professional & Technical Skills: - Must To Have Skills: Proficiency in ServiceNow.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 7.5 years of experience in ServiceNow.- This position is based at our Chennai office.- A 15 years full-time education is required. Qualification 15 years full time education

Role Description This is a contract hybrid role for a Quantitative Developer The Quantitative Developer will be responsible for tasks related to Trading, Quantitative Analytics, Quantitative Finance, Mathematics, and Statistics. Responsibilities Develop, implement, and maintain quantitative models and algorithms for trading, risk management, and financial analysis. Design and build high-performance systems for trading and financial applications. Collaborate with quantitative analysts, traders, and other stakeholders to understand business requirements and translate them into technical solutions. Write efficient, robust, and well-documented code in C++ and/or C#. Optimize existing code and systems for performance and scalability. Conduct thorough testing and validation of models and systems. Contribute to the development of software development best practices. Support the integration of new algorithms into existing trading infrastructure. Conduct code reviews, assist in troubleshooting, and debug issues in production systems. Participate in the documentation of processes and systems. Qualifications Experience in Trading, Quantitative Analytics, and Quantitative Finance. Proficiency in programming languages such as C++ and C# (Must-have). Experience in financial markets and derivatives. Required Skills And Qualifications Minimum 3 years of professional programming experience in C# or C++. Strong expertise in implementing complex algorithms and high-performance systems. Solid understanding of efficient coding practices and optimization techniques. 3+ years of experience developing and supporting critical applications within financial institutions or extensive experience in similarly complex industries. Good understanding of financial domain concepts, systems, and tools. Experience with version control systems (e.g., Git). Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Key Skills C#, C++ Algorithms, High-Performance Computing Financial Applications System Optimization, Fintech, Hybrid Development Teams, Domain Collaboration. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Statistics, Financial Engineering, or a related quantitative field. Experience with scripting languages such as Python. Knowledge of database systems (SQL, NoSQL). Familiarity with cloud computing platforms (e.g., AWS, Azure). Experience with Agile development methodologies.

Performing factor, strategy, portfolio construction and risk model related research projects Ensure collected data is prepared for cleansing and factor analysis Analysing and interpreting data to identify trends and patterns Results interpretation, presentation of results to the team, and refinement of models based on feedback given. Running scripts / process for existing quants models Manager Selection Portfolio construction Reporting – assimilation of data and preparation of decks Tech Stack – R / Python + SQL Dashboards + website – UX / UI – React / Java Script / HTML +

Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. This role is part of the Home team within the Product Analytics and Experimentation organization. The team supports the Product team by providing insights and incrementally measurement to help inform decisions on product features. Our team is looking for an established performer who consistently applies analytical capabilities, principles, and playbooks to solve business problems, with moderate guidance and direction. The role involves regular interaction with stakeholders up to the Senior Manager level. In this role, you will: Extract and integrate data from multiple sources to support model building and analytics. Design and recommend both simple and complex experiments (e.g., A/B, pre/post, causal impact) to address business questions. Build basic models (e.g., linear, logistic, clustering) and select appropriate data structures and formats. Develop and maintain basic data pipelines and workflows that support modeling tasks. Work with stakeholders in an iterative, collaborative process to refine project scope and requirements. Apply business knowledge to shape modeling questions, select features, and guide decisions. Deliver clear and concise data stories and visualizations that support decision-making. Automate recurring reporting and dashboarding tasks across multiple platforms (web, app, geo). Share documentation, code, and project artifacts (e.g., executive summaries, tech docs, visualizations) with relevant audiences. Communicate project goals, methods, caveats, and insights to both technical and non-technical stakeholders. Collaborate openly with analytics peers through brainstorming, peer review, and knowledge sharing. Train and enable stakeholders to use dashboards and self-service tools; promote data literacy. Troubleshoot and resolve data issues and ensure efficient query and pipeline performance. Uphold best practices for code sharing and documentation using tools like GitHub, IEX, and Confluence. Continuously seek feedback and apply it to improve current and future projects. Experience and qualifications: Experience 1-2 years of experience in a data analytics role for Bachelor s/Master s graduates (preferably in Mathematics or a scientific discipline), or 2+ years in a comparable professional setting. Proven track record of delivering data-driven insights and recommendations that led to business impact or performance improvements. Technical Skills Intermediate proficiency in R , Python , or SQL for analyzing, structuring, and visualizing large datasets. Competent in extracting, transforming, and combining data from multiple sources. Able to build basic models (e.g., linear/logistic regression, clustering) and support them with appropriate data formats. Experienced in writing efficient, reusable code and creating basic data pipelines. Familiarity with tools like GitHub, IEX, and Confluence for code sharing and documentation. Working knowledge of query optimization and data quality best practices. Statistical & Analytical Knowledge Basic understanding of probability, descriptive statistics (e.g., ANOVA, regression), and frequentist concepts. Ability to design and interpret experiments (e.g., A/B, pre/post, causal impact). Capable of framing business problems as analytical tasks and selecting suitable methodologies. Business & Domain Knowledge Strong business acumen with the ability to align analytics to strategic objectives. Understanding of key data sources, their business context, and appropriate use in modeling. Ability to identify relevant features and guide model design decisions. Communication & Collaboration Strong communication and influencing skills, with experience tailoring insights to both technical and non-technical audiences. Skilled in creating clear, audience-appropriate data visualizations, with awareness of inclusive design principles. Collaborative team player open to feedback, peer review, and knowledge sharing. Mindset & Problem Solving Demonstrated critical thinking and curiosity with a proactive, solutions-focused approach. Comfortable working iteratively and independently, adjusting based on feedback and findings. Strong skills in information gathering, problem solving, and continuous learning. Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request . We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Groups family of brands includes: Brand Expedia , Hotels.com , Expedia Partner Solutions, Vrbo , trivago , Orbitz , Travelocity , Hotwire , Wotif , ebookers , CheapTickets , Expedia Group Media Solutions, Expedia Local Expert , CarRentals.com , and Expedia Cruises . 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. . Never provide sensitive, personal information to someone unless you re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs . Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.

Key Responsibilities Develop and implement a comprehensive analytics strategy aligned with organizational objectives. Lead cross-functional projects using advanced data modeling and analysis techniques to uncover strategic insights and process optimization opportunities. Design, build, and maintain data models, dashboards, reporting systems, and performance metrics to support key business decisions. Drive critical business processes such as demand forecasting and the Sales & Operations Planning (S&OP) process. Generate actionable sales recommendations for the trade sales team. Optimize business processes like supply chain networks and inventory management through predictive and prescriptive data modeling. Oversee the delivery of analytical reports and performance insights across functions. Manage and streamline processes related to data intake, validation, mining, engineering, visualization, and reporting. Anticipate and plan for future analytical needs related to people, technology, budgeting, and business objectives. Apply advanced analytics techniques to enhance commercial routines and decision-making. Lead data insight initiatives and ensure effective stakeholder collaboration. Clearly communicate the impact of analytics-driven insights across internal and external teams. Perform critical analysis and deliver actionable business recommendations. Educational Qualifications B.E./B.Tech/M.Tech in Computer Science, Statistics, Data Management, or Business Intelligence OR MBA/PGDM in Data Science, Business Analytics, Business Intelligence, Sales, or Marketing Work Experience Minimum 4+ years of experience in data analytics, including monitoring, managing, manipulating, and drawing insights from complex datasets. Proven track record working with data visualization tools such as Power BI, Tableau, Raw, or chart.js. Preferred/Additional Requirements Strong understanding of data mining principles, predictive analytics, and integrating data from multiple sources (on-premises and cloud-based). Experience with analytical and statistical techniques including hypothesis development, A/B testing, data analysis, and drawing conclusions. Ability to generate actionable insights and recommendations for business units. Team Structure Will work closely with multiple vendor teams . Key Interfaces Internal: Supply Chain, Sales, and Finance Teams External: Analytics vendors Functional Competencies Strong problem-solving and quantitative analysis skills Ability to manage multiple projects, processes, and cross-functional teams simultaneously Excellent collaboration, communication, and stakeholder management skills Behavioral Competencies Critical Thinking: Ability to evaluate complex issues, make informed decisions, and deliver innovative solutions Professionalism: Demonstrates integrity, accountability, strong work ethic, and ethical behavior

SUMMARY Open Position: FARMAR Responsibilities: Providing animals with food and water Ensuring the well-being of animals Engaging in agricultural activities and tending to palm trees Skills and Qualifications: Skilled in agricultural tasks Requirements Requirements: Capability to work on a farm At least 1 year of farming experience Benefits Specified Salary: 110 Accommodation and Meals: Accommodation is provided; meals are the worker’s responsibility. Working Hours: 10 hours per day Weekly Day Off: One day per week Required Languages: English Muslim or Christian.

About the Program Our internships center around hands-on mentorship , capstone project, interactive sessions, and small group discussions. As a data science intern for one of our three Data Science departments ( Health, Life Sciences and Research ) your activities will span one or more of the following researching state-of-the-art methods, designing, writing code and running experiments to test hypotheses, perform validation of the system , developing demo applications . You will work closely with the diverse team of data scientists and domain experts . During this internship, you ll be paired with a core expert group who will mentor you as you tackle real-world projects in respective domains . You ll also be able to access our physical and virtual educational resources, attend guest speakers and social events, and get a sense of what it would be like to work here full time. If you re thinking about a career in data science, technology, clinical analytics, life sciences, or research, look no more. If you have a curious mind, a collaborative nature, and a passion for solving interesting problems, we have a feeling you ll fit right in. About the Position As a Data Science intern, you ll work side by side with full time employees to learn how we identify market signals, analyze large datasets, build and test models, create new strategies, d emonstr ate technology proof-of- concepts and write code to implement them. The problems we work on rarely have clean, definitive answers, hence providing an opportunity to cross-collaborate. Through your experience we hope that you will better understand the diverse array of research challenges considered every day, from reasoning about how best to analyze very noisy datasets to building practical models using various state of the art technologies. Education and other qualifications Master or PhD in computer science, data science is r equired . Skills Strong understanding of ML/NLP pipelines , proficiency in Python . H ands-on project development experience with supervised and unsupervised learning; model building, validation, and testing using state of art ML algorithms such as random forest, SVM, Logistic Regression, Bayesian modeling would be a plus . Good to have experience or knowledge of building , fine-tuning and deploying deep learning models, neural networks, state-of-the-art transformer language models, GenAI . Experience or interest in working with big data and applying advanced algorithms in Health care, Life Sciences or any Research domains . Experience using *nix systems, open-source software, libraries and jupyter notebook hubs is required . Behaviors Ability to drive new developments and implement process changes and disruptive technologies in the organization. Self-motivated and a team player. Enjoys being part of an agile , global team with mem bers in India, Europe and the US . G reat collaborator. Good communication and documentation skills Adopts pragmatic approach when choosing and implementing the right technologies to solve a problem and develops success metrics. Thirsty for knowledge and keen to share learning s with the team . Elsevier is an equal opportunity employer qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form https / / forms.office.com / r / eVgFxjLmAK , or please contact 1-855-833-5120. Please read our Candidate Privacy Policy .

We are looking for a highly skilled and experienced Field Risk Officer to join our team at Equitas Small Finance Bank Ltd. The ideal candidate will have 1-5 years of experience in the BFSI industry. Roles and Responsibility Conduct risk assessments and evaluations to identify potential threats to the organization. Develop and implement strategies to mitigate risks and ensure compliance with regulatory requirements. Collaborate with cross-functional teams to monitor and manage risk exposure. Analyze market trends and competitor activity to inform risk management decisions. Provide expert guidance on risk management best practices to stakeholders. Identify and report on key performance indicators (KPIs) related to risk management. Job Requirements Strong understanding of risk management principles and practices. Excellent analytical and problem-solving skills. Ability to work effectively in a fast-paced environment and prioritize multiple tasks. Strong communication and interpersonal skills. Experience working with financial institutions or similar organizations. Knowledge of relevant regulations and standards, such as Basel II or CCAR/CECL. Additional Info The company offers a competitive salary and benefits package.

Strong proficiency in Python and/or R for data analysis and modeling. Advanced SQL skills for data querying and transformation. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of statistics, hypothesis testing, regression analysis, and data mining. Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Hadoop) is a plus. Excellent problem-solving skills and attention to detail.

Leads GLOBAL DATA SCIENCE ADVANCED ANALYTICS within the Analytics Continuum Conceptualizes and builds predictive modeling, simulations, and optimization solutions to address business questions or use cases Applies ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the business Conducts model validations and continuous improvement of the algorithms, capabilities, or solutions built Deploys models using Airflow, Docker on Google Cloud Platforms You connect the dots - Merge multiple data sources and build Statistical Models / Machine Learning models in Price and Promo Elasticity Modeling, Marketing Mix Modeling to derive actionable business insights and recommendation Assemble large, sophisticated data sets that meet functional / non-functional business requirements Build data and visualization tools for Business analytics to assist them in decision making You are a collaborator - Work closely with Division Analytics team leads Work with data and analytics specialists across functions to drive data solutions You are an innovator - Identify, design, and implement new algorithms, process improvements: while continuously automating processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Qualifications What you ll need BE/BTECH [ Computer Science, Information Technology is preferred ], MBA or PGDM in Business Analytics / Data Science, Additional DS Certifications or Courses, MSC / MSTAT in Economics or Statistics 5+ years of experience in building data models and driving insights Hands-on/experience on developing statistical models, such as linear regression, ridge regression, lasso, random forest, SVM, gradient boosting, logistic regression, K-Means Clustering, Hierarchical Clustering, Bayesian Regression etc. Hands on experience on coding languages Python(mandatory), R, SQL, PySpark, SparkR Strong Understanding of Cloud Frameworks Google Cloud, Snowflake and services like Kubernetes, Cloud Build, Cloud Run. Knowledge of using GitHub, Airflow for coding and model executions and model deployment on cloud platforms Working knowledge on tools like Looker, Domo, Power BI and web apps framework using plotly, pydash, sql Experience front facing Business teams (Client facing role) supporting and working with multi-functional teams in a dynamic environment What you ll need (Preferred) Managing, transforming, and developing statistical models for RGM/Pricing and/or Marketing Effectiveness Experience with third-party data i.e., syndicated market data, Point of Sales, etc. Working knowledge of consumer packaged goods industry Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Experience visualizing/presenting data for partners using: Looker, DOMO, pydash, plotly, d3.js, ggplot2, pydash, streamlit etc Willingness and ability to experiment with new tools and techniques Ability to maintain personal composure and thoughtfully handle difficult situations. Knowledge of Google products (BigQuery, data studio, colab, Google Slides, Google Sheets etc)

Responsibilities Lead the design, development, and deployment of machine learning and GenAI models with a strong focus on AWS AI architecture. Collaborate with cross-functional teams to identify business opportunities and develop data-driven solutions. Provide technical leadership and mentorship to the data science team. Conduct research and stay updated on the latest advancements in machine learning and artificial intelligence. Drive the implementation of best practices for data collection, preprocessing, and model evaluation. Communicate effectively with stakeholders to understand their requirements and translate them into actionable data science projects. Contribute to the development of data science strategies and roadmaps. Skill Requirements A minimum of 10+ years of experience in data science, with a focus on machine learning and artificial intelligence. Proven track record of leading and delivering complex data science projects. Expertise in building and deploying machine learning and GenAI models at scale using AWS AI services. Strong programming skills in languages such as Python, R, or Java, with proficiency in leveraging AWS AI SDKs and APIs. In-depth knowledge of statistical modeling, data mining, and predictive analytics. Mandatory Skills: Data Science. Experience5-8 Years.

We are currently seeking an experienced professional to join our team in the role of Senior Analyst - Decision Science Principal responsibilities Undertake model validation and testing activities as dictated by the Global Model Risk Policy including the assessment of; model inputs, calculations, reporting outputs, conceptual soundness of the underlying theory and the suitability of the use for its intended purpose, relevance and completeness of data, qualitative information and judgements, documentation, and implementation of the model. Provide written reports detailing the results of validations highlighting issues identified during the validation. Validate remediation activities completed by the ILOD to ensure appropriate resolution of identified issues. Communicate technical model related information and results to Model Owners and Model Users through the course of a validation. Contribute to management, regulatory, and external confidence in all models used across the group. Deliver, high quality, timely validation reports that add value to the business. Requirements Experience on Retail Credit Risk model development/validation specifically comprising stress testing models (example: CCAR, PRA etc.) and reserving models such as CECL and IFRS9. Preferably familiar with different Retail PD/LGD/EAD model development methodology and its validation for different retail portfolios such as Credit Cards, Mortgage, PIL, etc. Strong statistical knowledge with hands on working experience in various modelling techniques such as linear regression, logistic regression, time series modelling, survival models etc. Sound understanding of different Retail portfolios such as Credit Cards, Mortgage, PIL, etc. Familiarity with OCC/FRB, EBA, ECB, UAE Guidelines and PRA regulations and k nowledge of Risk models, performance metrics and risks and associated issues. Some knowledge of internal procedures and local regulations and those of other country regulators would be an advantage. Minimum 1-5 years of experience of model validation/development experience in Risk Management in Retail domain Experience with some statistical modelling software / programming language e.g. SAS, Python, R, Matlab, C++, VBA. Experience of developing and reviewing models throughout the customer lifecycle and conducting independent model reviews is beneficial. Good written and verbal communication skills. Team-oriented mentality combined with ability to complete tasks independently to a high-quality standard. Master s or PhD degree in a quantitative discipline like Financial Mathematics, Statistics, Econometrics, Quantitative Finance, Economics or Engineering. Support the management of model risk across a large complex banking group and m anage model risk whilst significant transformational activity is being implemented, both regionally and globally.

About The Role : In Scope of Position based Promotions (INTERNAL only) Job Title:Quantitative Strategist Analyst Location:Mumbai, India Role Description Group Strategic Analytics : Analytics and technology are seen as central to all the main units of the bank, including Investment Bank, Corporate Bank and to Risk and Control functions. The Strategic Analytics team combines expertise in quantitative analytics, modelling, pricing and risk management with deep understanding of system architecture and programming. The primary output is a scalable and flexible Front Office pricing and risk management system with consistent interface to both the Middle Office and Back Office. The consistency in analytics and the technology platform ensures that no arbitrage can exist between various parts of the Bank as well as rational allocation of constrained resources, including risk budget, balance sheet, funding, and capital. What we'll offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities Valuation Control Strats: The candidate is required to work in collaboration with London/New York/Berlin team on various quantitative and regulatory driven projects. Candidate is required to understand the business problem, gather information required for the implementation and provide an end-to-end optimized solution on a scalable platform. Implementation of the project needs to be done in Python programming language. Candidate should possess a very good English communication skill in order to coordinate and communicate work effectively with various stakeholders spread across globe. ROLE RESPONSIBILITIES Development of complex processes, framework or risk analysis as well as improvements Implement, enhance and maintain existing framework to measure market risks across the bank Understand and decipher business problem to convert into manageable smaller problem statements Coordinate and gather information from various stakeholders for deeper understanding of the business Design an automated solution which is optimized and scalable Develop and design tables and databases required for the storage of the data Develop applications/libraries for the implementation of the solution Remediation of regulatory as well as external and internal findings against the MR HS models in line with the assigned tasks Constant awareness and understanding of the key market risks taken by the business areas and communication to senior management and with external stakeholders, challenge the business within assigned areas when required Quality assurance (e.g. 4 eyes principle reviews) Your skills and experience Education/ Qualifications: Strong educational background in Engineering/Science, Economics, Statistics or other numerate discipline preferably from good colleges in India e.g. IIT, NIT, ISI , BITS etc. Good knowledge of financial instruments and markets across all asset classes Knowledge of financial pricing models, risk models would be desirable Certification courses like CFA/FRM/CQF Competencies: Programming Skills At least 2 years hands on experience in Python programming Good knowledge of OOPs programming concepts ( Class, Pointers, Data structure stacks, queue) Experience in pulling data from various Market data sources. Independent handling and mitigating methodological or process weaknesses identified by regulators, auditors and internal model validation team Strong communication skills and presentation ability with attention to detail Good problem solving instincts and strong analytical skills Personal characteristics: Ability to work independently as well as flexibly within intra or inter-departmental groups Continuous advancement of own skills and knowledge Can-Do attitude & Able to cope well under pressure and tight deadlines How we'll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About us and our teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

Job Title 4G LTE Optimization Expert Experience 7 to 8 yrs Notice period 15 days Location Noida About The Role : We are seeking highly skilled and experienced 4G LTE Optimization Experts to join our team. The ideal candidate will have a strong understanding of 4G LTE network technologies, optimization techniques, and troubleshooting methodologies. Key Responsibilities : Network Performance Optimization : - Analyze network performance metrics (KPIs) to identify areas for improvement. - Optimize network parameters to enhance coverage, capacity, and quality of service. - Troubleshoot network issues and implement corrective actions. - Conduct drive tests and analyze data to identify network performance bottlenecks. Radio Network Planning and Design : - Participate in radio network planning and design activities, including site selection, frequency planning, and antenna configuration. - Perform RF propagation modeling and simulations to predict network performance. Network Configuration and Maintenance : - Configure and maintain 4G LTE network elements, including base stations, core network equipment, and transport networks. - Implement software upgrades and patches to ensure optimal network performance. Troubleshooting and Problem Solving - Diagnose and resolve complex network issues, including radio interference, handover failures, and capacity bottlenecks. - Utilize network management tools and diagnostic techniques to identify and isolate problems. Documentation and Reporting : - Prepare detailed technical documentation, including network design documents, optimization reports, and troubleshooting reports. - Present findings and recommendations to technical and non-technical audiences. Required Skills and Experience : - Strong understanding of 4G LTE technologies, including LTE-Advanced features. - Hands-on experience with network optimization tools and techniques. - Proficiency in using network management systems (e.g., NetAct, OSS). - Knowledge of RF propagation principles and RF optimization tools. - Excellent analytical and problem-solving skills. - Strong communication and interpersonal skills. - Ability to work independently and as part of a team. - 7-8 years of total experience with 4-5 years in LTE. Preferred Qualifications : - Certification in 4G LTE technologies (e.g., Nokia, Ericsson). - Experience with 5G NR technologies. - Knowledge of network automation and orchestration tools. If you are a passionate and dedicated 4G LTE Optimization Expert, we invite you to join our team and contribute to the success of our network. Apply Insights Follow-up Save this job for future reference Did you find something suspiciousReport Here! Hide This Job Click here to hide this job for you. You can also choose to hide all the jobs from the recruiter.

About Emperen Technologies : Role Description : This is a contract hybrid role for a Quantitative Developer. The Quantitative Developer will be responsible for tasks related to Trading, Quantitative Analytics, Quantitative Finance, Mathematics, and Statistics. Responsibilities : - Develop, implement, and maintain quantitative models and algorithms for trading, risk management, and financial analysis. - Design and build high-performance systems for trading and financial applications. - Collaborate with quantitative analysts, traders, and other stakeholders to understand business requirements and translate them into technical solutions. - Write efficient, robust, and well-documented code in C++ and/or C#. - Optimize existing code and systems for performance and scalability. - Conduct thorough testing and validation of models and systems. - Contribute to the development of software development best practices. - Support the integration of new algorithms into existing trading infrastructure. - Conduct code reviews, assist in troubleshooting, and debug issues in production systems. - Participate in the documentation of processes and systems. Qualifications : - Experience in Trading, Quantitative Analytics, and Quantitative Finance. - Proficiency in programming languages such as C++ and C# (Must-have). - Experience in financial markets and derivatives. Required Skills and Qualifications : - Minimum 3 years of professional programming experience in C# or C++. - Strong expertise in implementing complex algorithms and high-performance systems. - Solid understanding of efficient coding practices and optimization techniques. - 3+ years of experience developing and supporting critical applications within financial institutions or extensive experience in similarly complex industries. - Good understanding of financial domain concepts, systems, and tools. - Experience with version control systems (e.g., Git). - Strong analytical and problem-solving skills. - Excellent communication and collaboration skills. Key Skills : - C#, C++ - Algorithms, High-Performance Computing - Financial Applications - System Optimization, Fintech, Hybrid Development Teams, Domain Collaboration. Preferred Qualifications : - Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Statistics, Financial Engineering, or a related quantitative field. - Experience with scripting languages such as Python. - Knowledge of database systems (SQL, NoSQL). - Familiarity with cloud computing platforms (e.g., AWS, Azure). - Experience with Agile development methodologies. Apply Insights Follow-up Save this job for future reference Did you find something suspiciousReport Here! Hide This Job Click here to hide this job for you. You can also choose to hide all the jobs from the recruiter.

Company Description : Emperen Technologies is a consulting company founded in 2010 with a focus on delivering real results for clients. The company has helped implement the vision of numerous Fortune 500, non-profit, and startup companies, demonstrating that a client-focused, values-driven consulting organization can be successful in the marketplace. Emperen offers scalability and flexibility to navigate and succeed in a complex technological landscape through a seamless delivery model tailored to each client's unique challenge. The team at Emperen continues to grow driven by demand and a commitment to continuous improvement. Role Description : This is a contract role for a Quant Developer at Emperen Technologies. The Quant Developer will be responsible for trading analysis, quantitative analytics, quantitative finance, mathematics, and statistics. This role is located on-site in Bengaluru. Qualifications : - 3+ years professional programming experience in C# or C++. - 3+ years developing and supporting critical applications in financial institutions or considerable experience in other areas/industries. - BSc in a scientific discipline such as Computer Science, Mathematics, Physics, or Engineering. - Higher degree (MSc or PhD) in a scientific discipline. - Quant Developers need strong programming skills to implement complex algorithms and models. - C# and C++ are commonly used in financial applications for their performance and efficiency. - Quant Developers often work on similar financial applications, requiring a deep understanding of financial systems and tools. - A strong foundation in a scientific discipline is crucial for understanding and developing quantitative models and algorithms. - Advanced degrees often provide deeper knowledge in quantitative methods, which is beneficial for complex financial modeling. Nice to have : - Experience designing/building end-user interfaces (e.g., risk visualization, pricing). - Experience working with Quantitative analysts. - Familiarity with other programming languages (Python, C++). - Knowledge of pricing theory and financial engineering. - Knowledge of grid computing (MS HPC) or Azure Batch. - Data Science knowledge/experience. - Familiarity with continuous delivery/integration using Team City and GitHub. Apply Insights Follow-up Save this job for future reference Did you find something suspiciousReport Here! Hide This Job Click here to hide this job for you. You can also choose to hide all the jobs from the recruiter.

About The Role : In Scope of Position based Promotions (INTERNAL only) Job TitleGroup Strategic Analytics Quantitative Strategist Specialist, AVP LocationMumbai, India Role Description We are seeking a highly motivated and skilled Techno- Functional specialist to join our Market Risk Strats team within GSA. This team comprised of people with technology, front office quant and market risk and methodology experience. This role offers a unique opportunity to bridge the gap between quantitative finance & technology. You will be responsible for leveraging your strong Python programming skills to develop, implement and maintain analytical tools and systems for monitoring and managing market risk. Your deep understanding of market risk metrics will be crucial in translating business requirements into technical solutions and ensuring the accuracy and efficiency of our risk management processes. Our People Our people are outstanding individuals with agile minds, from a diverse range of backgrounds and cultures. They generate fresh ideas and innovative solutions which set us apart from our competitors and add value to our clients. Group Strategic Analytics (GSA) Analytics and technology are seen as central to all the main units of the bank, including Investment Bank, Corporate Bank and to Risk and Control functions. The Strategic Analytics team combines expertise in quantitative analytics, modelling, pricing and risk management with deep understanding of system architecture and programming. The primary output is a scalable and flexible Front Office pricing and risk management system with consistent interface to both the Middle Office and Back Office. The consistency in analytics and the technology platform ensures that no arbitrage can exist between various parts of the Bank as well as rational allocation of constrained resources, including risk budget, balance sheet, funding, and capital. What we'll offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities Reporting Development (Python)Design, develop, and maintain automated market risk reports, dashboards, and analytics tools using Python and relevant libraries (e.g., Pandas, NumPy, Matplotlib). Market Risk ExpertiseApply a strong understanding of market risk concepts, including VaR, stress testing, sensitivity analysis, and regulatory reporting requirements (e.g. Basel accords, CRR). Control Framework Enhancement (Python)Utilize Python to build and implement data quality checks, monitoring tools, and automated controls to strengthen the market risk control environment. Data ManagementWork with large datasets, ensuring data integrity, accuracy, and timely availability for risk reporting and analysis. Experience with data warehousing and database technologies (e.g., SQL) is a plus. Stakeholder CollaborationPartner effectively with market risk managers, front office trading desks, IT teams, and other relevant stakeholders to understand business requirements and translate them into technical solutions. Process ImprovementIdentify opportunities to streamline existing market risk processes through automation and the application of technology. DocumentationCreate and maintain clear and concise technical documentation for developed reports, tools, and processes. Project ManagementParticipate in and potentially lead projects related to market risk reporting and technology initiatives. Regulatory AwarenessStay abreast of relevant market risk regulations and incorporate them into reporting and control frameworks. Troubleshoot and resolve technical issues related to market risk systems and applications. Participate in system testing, user acceptance testing (UAT) and audit reviews. Your skills and experience Bachelor's or Master's degree in a quantitative field such as Finance, Economics, Mathematics, Statistics, Computer Science, or a related discipline. Minimum of 8-10 years of experience in a market risk role within a financial institution. Strong proficiency in Python programming with hands-on experience in developing data-driven applications, reports, and analytics. Solid understanding of market risk methodologies, models, and metrics. Experience with financial data vendors and APIs. Excellent analytical, problem-solving, and quantitative skills. Strong communication and presentation skills, with the ability to explain technical concepts to both technical and non-technical audiences. Ability to work independently and as part of a team in a fast-paced environment. Familiarity with database technologies (e.g., SQL) is desirable. How we'll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs

Job Summary Data scientist Co-ordinate tasks/deliverables within the team Apply data science techniques such as machine learning statistical modeling and artificial intelligence Responsibilities Technology SPOC responsible for solution design Work with the business and technical system client stakeholder to understand current application pains architecture. He will help in building the Architectural blue print Help to define/propose architectures tech stack. Help to define/propose the Machine Learning Algorithms and models. Manage a team of data scientists machine learning engineers Help the Project Manager with work breakdown structure and User Story definitions Co-ordinate tasks deliverables within the team Apply data science techniques such as machine learning statistical modeling and artificial intelligence Measure and improve results Present Final results to stake holders Primary skills: Data science Python AIML GEN AI NLP GCP stack Secondary skills: Pharmacy domain and Data engineering skills

We are looking for an ambitious self-starter with a strong track record of delivering results. This role will put you in the middle of the action, requiring you to tackle complex challenges in a rapidly-scaling startup. You will work cross-functionally to generate product insights in our direct-to-consumer business. Through critical thinking and analytical rigor, you will understand user behavior and engagement, enabling us to innovate on our product. You will also provide visibility into performance drivers, empowering leaders to make data-supported decisions. If you thrive in a fast-paced, mission-driven, and impact-oriented environment, we encourage you to apply! Duties and Responsibilities: Work closely with PMs to define feature goals and lead A/B testing and experimentation initiatives, including designing tests, tracking events and properties, and analyzing results to understand attribution, causation, and incremental lift Proactively generate exploratory analyses and in-depth research on large data sets to help product teams uncover high-impact opportunities Use your wizardly data querying and visualization skills to answer any question in a way that provides actionable insights Develop easy-to-consume dashboards and frameworks to monitor and visualize KPIs Influence strategic changes by presenting insights and recommendations to various organizational levels, including executives Collaborate with data engineers to maintain consistent business logic throughout the organization Foster a data-driven, test-and-learn culture with your passion for storytelling through data and surfacing insights via analytics, experimentation, and research into the user journey and customer funnel Qualifications and Skills: 7+ years of experience in data analysis, data science, and/or data-driven product management Expert knowledge of SQL Expertise with data visualization tools to convey actionable insights to product managers and business leaders Experience in A/B testing and experimentation best practices Knowledge of basic statistical techniques; linear and logistic regression, confidence intervals Familiarity with a scripting language like Python or R Proven ability to work independently, multi-task, and thrive in a fast-paced environment

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :Noida/Gurugram/Bangalore Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

We are looking for a Data Scientist to help us gain useful insight out of raw data. Data Scientist responsibilities include working with the data science team, planning projects and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If youre also able to align our data products with our business goals, we’d like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data. Key Responsibilities Responsible for overseeing the data scientists’ team and data specialists Teach, lead, and counsel colleagues on new techniques or solutions Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem Responsible for the conception, planning, and prioritizing of data projects Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques Ensure that data projects align with organizational goals Minimum Qualification Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field 10+ years of experience solving analytical problems using quantitative approaches