410 Logistic Regression Jobs - Page 3

About Info Edge InfoEdge’s mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behavior, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. About BU: Corporate Function – Data Science Designation: AI Scientist Desired Experience: 0-3 Year Required Educational Qualification : PhD/ M.Tech / B.Tech with relevant experience from Tier 1 Campus As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs. Why Join us: This is a unique opportunity to work on innovative and disruptive technologies that are shaping the future of the industry. We are looking for candidates who are willing to work passionately in a fast- paced environment and are ready to enhance their skills by learning something new. Being a part of the InfoEdge team, you will be engaged in innovations, product development, integration with mobile and social media, technology, research and development, quality assurance, sales and marketing. To learn more about Info Edge visit http://www.infoedge.in/

Salary : 30 to 45 LPA Exp: 6 to 10 years Location :Hyderabad (Hybrid) 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 5+ 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.

As an Application Developer, you will design, build, and configure applications to meet business process and application requirements. Your responsibilities include ensuring the smooth functioning of applications, addressing any arising issues, collaborating with the team, making team decisions, and engaging with multiple teams. Your problem-solving abilities and expertise in SAP Global Trade Services will be crucial in contributing to the success of the project. You are expected to be a Subject Matter Expert (SME) and manage the team to perform effectively. Your role involves making team decisions, contributing to key decisions, providing solutions to problems within and across multiple teams, and ensuring the applications" smooth operation. Proficiency in SAP Global Trade Services, statistical analysis, machine learning algorithms, data visualization tools like Tableau or Power BI, and hands-on experience with various machine learning algorithms are essential. Additionally, you should have a strong grasp of data munging techniques to maintain data quality and integrity. The ideal candidate should possess a minimum of 7.5 years of experience in SAP Global Trade Services. This full-time position is based in Hyderabad and requires a 15 years full-time education.,

Minimum qualifications: You have a Bachelor's degree in Electrical Engineering or a related field, or equivalent practical experience. Along with that, you possess 4 years of experience with physical design flow, including floor planning, place and route, or physical verification. Your expertise also includes experience with low-power design techniques like power gating, clock gating, or voltage scaling. Preferred qualifications: It is preferred that you have experience in using Machine Learning (ML) in physical design. You also have knowledge of machine learning algorithms ranging from logistic regression to deep neural networks and reinforcement learning, coupled with proficiency in data structures and algorithms. About the job: As a member of our team, you will be part of a group that consistently pushes boundaries, working on developing custom silicon solutions that drive the future of Google's direct-to-consumer products. You will play a pivotal role in the innovation behind products that are beloved by millions globally. Your expertise will be instrumental in shaping the next era of hardware experiences, ensuring unparalleled performance, efficiency, and integration. In this role, you will be responsible for contributing to the enhancement of Power Performance Area (PPA) through the utilization of machine learning techniques. Leveraging your experience in physical design and machine learning, you will tackle technical challenges and enhance Power, Performance, Area, and Schedule metrics. Your tasks will involve design and optimizations, floor planning, place and route, clock and power planning, timing analysis, and Power Delivery Network (PDN) analysis. Collaboration is key in this role, as you will work across Alphabet, engaging with design, CAD, and machine learning teams. Google's mission revolves around organizing the world's information, making it universally accessible and useful. Our team amalgamates the finest aspects of Google AI, Software, and Hardware to craft profoundly useful experiences. We delve into research, design, and development of cutting-edge technologies and hardware to accelerate computing, ensuring it is seamless and potent. Our ultimate goal is to enhance people's lives through technology. Responsibilities: Your responsibilities will include deploying Artificial Intelligence (AI) solutions into chip design, collaborating with internal teams, Google DeepMind, and others to explore solutions and enhance chip design PPA or cycle time.,

The role within Niro Money, Data and Analytics team involves translating data into actionable insights to enhance marketing ROI, business growth, and customer experience for various financial products like personal loans, home loans, credit cards, and insurance. You will be required to have a strong background in data analytics and deliver strategic recommendations to key stakeholders and business heads. You will lead, mentor, and develop a high performing team of data analysts and data scientists focused on building decision science models and segmentation to predict customer behaviors. Additionally, you will develop data-driven strategies to optimize marketing ROI for different financial products such as personal loans and credit cards. Collaborating with the Partnership & Marketing team, you will conduct marketing experiments to improve funnel conversion and measure the effectiveness of marketing campaigns and experiments, recommending necessary changes to enhance customer journey-related product changes. In this role, you will foster a culture of collaboration, innovation, and data-driven decision-making across multiple teams within Niro. Managing multiple analytics projects simultaneously, you will prioritize them based on potential business impacts and ensure timely and accurate project completion. You will also be responsible for project planning and monitoring, promptly addressing challenges to keep projects on track. Additionally, you will partner with Data Engineering, Technology, and Product teams to develop and implement data capabilities for running marketing experiments and delivering actionable insights at scale. The ideal candidate for this role should possess a Master's degree in statistics, mathematics, data science, economics, or BTech in computer science or engineering. You should have at least 5 years of hands-on experience in decision science analytics and building data-driven strategies, preferably in the financial services industry. Additionally, you should have 2+ years of experience in managing and leading a team of data analysts and data scientists, as well as hands-on experience in statistical model development using Python packages like Scikit learn, XGBoost, Stats models, or decision tree tools. Proficiency in SQL and Python is essential, along with a proven track record of decision-making and problem-solving based on analytics. Experience with Snowflake, AWS Athena/S3, Redshift, and BI Tools like AWS Quicksight would be advantageous. You should have a strong analytical mindset, the ability to evaluate complex scenarios, and make data-driven decisions. Being creative and curious with a willingness to learn new tools and techniques is crucial. A data-oriented personality, along with excellent communication and interpersonal skills to collaborate effectively with diverse stakeholders, will be key to success in this role.,

We are looking for a skilled Senior Data Analyst to join our team at Hevo Data, responsible for driving business growth through data-driven insights. The ideal candidate will have a strong background in data analysis and interpretation, with excellent communication skills. Roles and Responsibility Develop and maintain complex data models and dashboards to support business decision-making. Analyze large datasets to identify trends, patterns, and correlations, providing actionable recommendations. Collaborate with cross-functional teams to design and implement data-driven solutions. Create reports and presentations that communicate findings and insights to stakeholders. Stay up-to-date with industry trends and emerging technologies in data analytics. Provide expert-level support for data-related projects and initiatives. Job Requirements Proven experience as a Senior Data Analyst or similar role, with a minimum of 2 years of experience. Strong proficiency in data analysis tools such as SQL, Excel, or statistical software. Excellent analytical, problem-solving, and communication skills. Ability to work effectively in a fast-paced environment with multiple priorities. Strong understanding of data structures, algorithms, and software design patterns. Experience working with large datasets and developing scalable data solutions.

Strong proficiency in Python.Experience with Large Language Models.Familiarity with machine learning and artificial intelligence.Experience with Google cloud platform. Required Candidate profile Desired Skills:Python, Artificial Intelligence, Machine learning, GCP Position Name: Data Scientist Client Name:Renault Work Location: Chennai Mode of Work : Hybrid

We are looking for a highly skilled Quant Researcher to join our team at QuantInsti, a leading quantitative learning company in the IT Services & Consulting industry. The ideal candidate will have a strong background in quantitative research and analysis, with excellent problem-solving skills and attention to detail. Roles and Responsibility Conduct thorough quantitative analysis of complex data sets to identify trends and patterns. Develop and implement advanced statistical models and algorithms to solve real-world problems. Collaborate with cross-functional teams to design and execute experiments and studies. Analyze and interpret large datasets to inform business decisions and drive growth. Stay up-to-date with industry trends and developments in quantitative research. Communicate complex technical concepts effectively to non-technical stakeholders. Job Requirements Strong proficiency in programming languages such as Python or R. Experience with data visualization tools like Tableau or Power BI. Excellent understanding of statistical concepts and machine learning algorithms. Strong analytical and problem-solving skills with attention to detail. Ability to work collaboratively in a team environment and communicate effectively. Strong organizational and time management skills with the ability to prioritize tasks.

Associate Economics Analyst, North America (NAM) Overview The Mastercard Economics Institute (MEI) is an economics lab powering scale at Mastercard by owning economic thought leadership in support of Mastercard s efforts to build a more inclusive and sustainable digital economy MEI was launched in 2020 to analyze economic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers The Institute is composed of a team of economists and data scientists that utilize synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentation, global thought leadership, media participation, and commercial work through the company s product suites About the Role We are looking for an economic analyst to engage in on-soil data analytics and economic research for the European region. This individual will report to the Vice President, Lead Economist, NAM, and will have the following responsibilities: Support client and stakeholder engagements for MEI across NAM Support collaboration with external clients, academic institutions, and industry partners. Develop and test hypotheses at the intersection of economics and retail and commerce. Assist in structuring work at the stream or small project level. Identify creative analyses and develop proprietary diagnostic indices by analyzing large and complex datasets, including big data and macroeconomic data Generate initial insights to help create effective, impactful, and quality-assured storylines and visuals at the stream or small project level. Synthesize analyses into clear, sound recommendations. Outline and help write reports and draft client presentations at the work stream or project level. Enhance existing products and partner with internal stakeholders to create new solutions. Proactively seek new knowledge and structure project work to facilitate the capture of intellectual capital with minimal oversight Actively participate in new solution development and support thought leadership activities by building knowledge, know-how, and best practices related to RC economic research; share and leverage to continuously improve quality and productivity. All About You Bachelors degree in Economics (preferred), Statistics, or Mathematics. Proficiency in SQL and data visualizations Ability to think critically and problem solve, willingness to learn Excellent communication Expertise in R, Python, or other major programming language is essential Experience using data visualization tools like Tableau / Power BI. Knowledge of JavaScript for visualization is a plus. Proficiency in key econometric and statistical techniques such as predictive modeling, logistic regression, survival analysis, time series modeling, design of experiments, decision trees, and data mining methods desirable

Key Responsibilities:Design, develop, and maintain advanced dashboards and reports in Tableau that provide insights into user engagement, product performance, and business metrics.Utilize Databricks to process, clean, and analyze large volumes of data efficiently.Develop complex SQL queries and optimize data pipelines for analytics workflows.Collaborate with cross-functional teams to define key metrics, data requirements, and analytical approaches.Conduct deep-dive analyses and present findings with clear data storytelling to influence product and business strategies.Automate routine reporting and data validation tasks to ensure accuracy and timeliness.Mentor junior analysts and promote best practices in data visualization and analytics.Stay current with latest trends and tools in data analytics, visualization, and big data platforms.

We are looking for a highly motivated and talented Junior Data Scientist to join our team at AGR Knowledge Services Pvt Ltd. The ideal candidate will have 2-4 years of experience in the field. Roles and Responsibility Collaborate with cross-functional teams to design and develop data-driven solutions. Analyze complex data sets to identify trends and patterns, providing actionable insights. Develop and maintain databases, data systems, and data pipelines. Design and implement machine learning models and algorithms to solve business problems. Work closely with stakeholders to understand business needs and develop targeted solutions. Stay up-to-date with industry trends and emerging technologies in data science. Job Requirements Strong foundation in statistics, mathematics, and computer science. Proficiency in programming languages such as Python, R, or SAS. Experience with data analysis tools such as SQL, Excel, or Tableau. Knowledge of machine learning algorithms and deep learning techniques. Excellent communication and problem-solving skills. Ability to work in a fast-paced environment and meet deadlines.

We are looking for a highly motivated and talented Junior Data Scientist to join our team at AGR Knowledge Services Pvt Ltd. The ideal candidate will have 2-4 years of experience in the field. Roles and Responsibility Collaborate with cross-functional teams to design and develop data-driven solutions. Analyze complex data sets to identify trends and patterns, providing actionable insights. Develop and maintain databases, data systems, and data pipelines. Design and implement machine learning models and algorithms to solve business problems. Work closely with stakeholders to understand business needs and develop targeted solutions. Stay up-to-date with industry trends and emerging technologies in data science. Job Requirements Strong foundation in statistics, mathematics, and computer science. Proficiency in programming languages such as Python, R, or SAS. Experience with data analysis tools such as SQL, Excel, or Tableau. Knowledge of machine learning algorithms and deep learning techniques. Excellent communication and problem-solving skills. Ability to work in a fast-paced environment and meet deadlines.

Department - Commercial DD&IT GBS Are you passionate about leading complex IT programs? Do you thrive in a dynamic environment where strategic thinking, collaboration, and innovation come together? If you have a proven track record in IT Program Management and are ready to make a difference, we want to hear from you! We are seeking a senior IT Program Manager to lead a large-scale, complex Customer Engagement ecosystem program supporting the HCP Engagement at a global environment (excluding USA). The role will focus on modernization and migration of the Customer Engagement ecosystem, integrating with portals, analytics and marketing platforms ensuring aligned delivery across business, markets, and technology stakeholders within a matrix organization. Read on and apply today for a life-changing career. Apply Now! The position As a Sr Program Manager HCP Engagements at Novo Nordisk, you will: Lead the planning, execution, and governance of IT programs to ensure successful outcomes. Lead the end-to-end delivery of Customer Engagement program including migration from legacy systems to newer technologies. Define and manage program plans, roadmaps, dependencies mapping, and milestones ensuring on-time, quality delivery aligned with business objectives. Drive complex integrations with other enterprise systems (e.g.: MDM, data warehouses, analytics, marketing automation, and HCP Portals). Engage with global and local business stakeholders (medical, commercial, compliance, data privacy) for requirements gathering, prioritization and alignment. Act as the primary escalation point for program risks, dependencies, and decision-making with senior leadership. Navigate a matrix environment while balancing global standards with local market needs. Drive execution of migration roadmaps including data migration, process harmonization, and change management planning. Collaborate with architecture and platform teams to ensure scalable, compliant configurations aligned with HCP engagement goals. Oversee validation, UAT, and cutover activities ensuring minimal business disruption. Manage vendor relationships including product implementation partners and system integrators. Proactively identify and mitigate delivery and operational risks. Ensure programs adhere to pharma quality, compliance (GxP, GDPR) and data privacy standards. Drive strategic alignment of IT initiatives with broader organizational goals. Establish clear project timelines, budgets, and deliverables, ensuring projects are delivered within scope, time, and budget. Facilitate communication and collaboration across cross-functional teams, including IT, business units, and external partners. Identify potential risks, develop mitigation strategies, and proactively address challenges. Champion digital transformation initiatives and promote the adoption of innovative digital solutions. Evaluate emerging technologies and recommend their integration into existing systems. Qualifications We are looking for a candidate who can bring the following skills and experience to the role: Bachelors degree in computer science, Information Technology, Business Administration, or a related field. A masters degree is preferred. Minimum 15+ years of experience in IT program management, with at least 12+ years in a senior or leadership role. Proven track record in managing complex digital and IT projects, including strategy development, implementation, and stakeholder engagement. Familiarity with IT infrastructure, software development lifecycles, and emerging digital technologies. Strong experience in budgeting, vendor management, stakeholder engagement, resource allocations etc. for large scale programs. Strong leadership and people management skills, with a consistent track record to build and lead impactful teams. Excellent communication, negotiation, stakeholder leadership and conflict resolution skills. Superb analytical and problem-solving skills with a focus on continuous improvement. Ability to engage, build and sustain trusted relationship both internally and externally. Proven track record of working in matrix setup of internal and external partner setup to deliver quality service management. Preferred Skills VEEVA/Salesforce certifications or formal training. Experience with CRM analytics and data migration tooling. Background in implementing CRM integrations with marketing automation platforms and content management systems. Experience in leading organizational change management alongside CRM rollouts.

Role & responsibilities Highly focused individual with self-driven attitude Problem solving and logical thinking to automate and improve internal processes Using various tools such as SQL and Python for managing the various requirements for different data asset projects. Ability to diligently involve in activities like Data Cleaning, Retrieval, Manipulation, Analytics and Reporting Using data science and statistical techniques to build machine learning models and deal with textual data. Keep up-to-date knowledge of the industry and related markets Ability to multitask, prioritize, and manage time efficiently Understand needs of the hiring organization or client in order to target solutions to their benefit Advanced speaking and writing skills for effective communication Ability to work in cross functional teams demonstrating high level of commitment and coordination Attention to details and commitment to accuracy for the desired deliverable Should demonstrate and develop a sense of ownership towards the assigned task Ability to keep sensitive business information confidential Contribute, positively and extensively towards building the organizational reputation, brand and operational excellence Preferred candidate profile 3-6 years of relevant experience in data science Advanced knowledge of statistics and basics of machine learning Experienced in dealing with textual data and using natural language processing techniques Ability to conduct analysis to extract actionable insights Technical skills in Python (Numpy, Pandas, NLTK, transformers, Spacy), SQL and other programming languages for dealing with large datasets Experienced in data cleaning, manipulation, feature engineering and building models Experienced in the end-to-end development of a data science project Strong interpersonal skills and extremely resourceful Proven ability to complete assigned task according to the outlined scope and timeline Good language, communication and writing skills in English Expertise in using tools like MS Office, PowerPoint, Excel and Word Graduate or Post-graduate from a reputed college or university

The Citi Analytics & Information Management (AIM) team, a global community, objectively connects and analyzes information to create actionable intelligence for business leaders. In partnership with the businesses, the team identifies fact-based opportunities for revenue growth and expense reduction. As a C12 (Individual Contributor) AVP within the Retail Bank Fraud Analytics team in Citi AIM, your primary focus will be to analyze transaction data, understand fraud patterns, and develop fraud loss mitigation strategies to minimize fraud losses and customer impact. You will be responsible for monitoring strategy performance, collaborating with the strategy implementation team, and proactively leveraging new data sources and advanced analytics techniques for fraud loss mitigation. Your role entails hands-on analysis on a regular and ad hoc basis, extracting various data sources, generating fraud risk insights, recommending business solutions, and monitoring strategy performance. It is essential to have a holistic view of different retail banking products, integrate analytical thinking with business knowledge, and utilize data analysis tools and methodologies to develop client-centric solutions. Proficiency in basic statistics, hypothesis testing, segmentation, and predictive modeling is required, along with expertise in decision tree (CHAID/CART), Logistic Regression, exploratory data analysis, SAS, SQL, Hive, Impala, and Excel. Knowledge of Python is desirable, and prior experience in Fraud Analytics is preferable. Familiarity with Tableau or any other data visualization tool is also advantageous. Experience in stakeholder management across functions and regions is necessary to translate data into consumer or customer behavioral insights, drive targeting and segmentation strategies, and effectively communicate with business partners and senior leaders. Strong presentation skills are essential for delivering clear presentations to share thoughts, solutions, or problems with stakeholders and senior management. Project management skills are required to create project plans, assign responsibilities, complete projects in a timely manner, and manage and report control issues transparently. You will be expected to support regulatory/audit activities and other risk and control activities as needed. Qualifications: - 8+ years of analytics experience, preferably in Fraud analytics - Advanced analytical and business strategy skills - Effective communication skills - Ability to present to business partners and leaders - Project and process management skills - Excellent written and verbal communication skills - Experience in financial services analytics - Strong organizational skills and ability to manage multiple projects simultaneously - Self-starter with the ability to work successfully in a team environment Education: - Bachelors/University degree or equivalent experience (Masters degree preferred),

The Staff ML Scientist position at Visa offers a unique opportunity to engage in cutting-edge Applied AI research within the realm of data analytics. As a key member of the team, you will play a pivotal role in driving Visa's strategic vision as a leading data-driven company. Your responsibilities will involve formulating complex business problems into technical data challenges, collaborating closely with product stakeholders to ensure the practicality of solutions, and delivering impactful prototypes and production code. You will have the chance to experiment with various datasets, both in-house and third-party, to evaluate their relevance to business objectives. Moreover, your role will encompass building data transformations for structured and unstructured data, exploring and refining modeling and scoring algorithms, and implementing methods for adaptive learning and model validation. Your expertise in automation and predictive analytics will be instrumental in enhancing operational efficiency and performance monitoring. In addition to your technical skills, you will be expected to possess a strong academic background and exceptional software engineering capabilities. A proactive and detail-oriented approach, coupled with excellent collaboration skills, will be essential for success in this role. This is a hybrid position, allowing for a flexible work arrangement that combines remote work and office presence. The expectation is to work from the office 2-3 set days per week, with a general guideline of being in the office at least 50% of the time based on business requirements. Qualifications: - 8 or more years of work experience with a Bachelors Degree or an Advanced Degree - Proficiency in modeling techniques such as logistic regression, Nave Bayes, SVM, decision trees, or neural networks - Ability to program in scripting languages like Perl or Python, and programming languages such as Java, C++, or C# - Familiarity with statistical tools like SAS, R, KNIME, and experience with deep learning frameworks like TensorFlow - Knowledge of Natural Language Processing and working with large datasets using tools such as Hadoop, MapReduce, Pig, or Hive - Publications or presentations in recognized Machine Learning and Data Mining journals/conferences would be advantageous Join Visa as a Staff ML Scientist and contribute to pioneering advancements in Applied AI research that drive innovation and shape the future of data analytics.,

Citi Analytics & Information Management (AIM) team is a global community that objectively connects and analyzes information to create actionable intelligence for business leaders. As a C12 (Individual Contributor) AVP within the Fraud Analytics team in Citi AIM, your primary focus will be on analyzing transaction data, understanding fraud patterns, and developing fraud loss mitigation strategies to minimize fraud losses and customer impact. You will be responsible for monitoring strategy performance, collaborating with the implementation team, and proactively leveraging new data sources and advanced analytics techniques for fraud loss mitigation. You will be expected to conduct hands-on analysis on a regular and ad hoc basis, extract various data sources beyond transactions, generate fraud risk insights, recommend business solutions, and monitor strategy performance. Proficiency in Logistic Regression/ ML Model development, regardless of the programming language, is essential. Your role will require thought leadership in designing, developing, and implementing Machine Learning solutions. Having a holistic view of retail banking products, best practices, and integrating analytical thinking with business knowledge is crucial. Experience in analytics within the BFSI domain, proficiency in basic statistics, hypothesis testing, segmentation, and predictive modeling are necessary. Strong skills in SAS, SQL, Hive, Impala, and Excel are expected, with knowledge in Python being desirable. Previous experience in Fraud Analytics and familiarity with Tableau or other data visualization tools are advantageous. Stakeholder management across various functions and regions, translating data into consumer insights, effective communication with business partners and senior leaders, and delivering clear presentations are key aspects of the role. You will also be responsible for project management, including creating project plans, assigning responsibilities, completing projects in a timely manner, and supporting regulatory/audit activities and risk control efforts when required. Qualifications: - 8+ years of analytics experience, including model development, with prior Fraud analytics experience preferred - Good knowledge of Python, SQL, and Big Data, with familiarity in ML/DL applications like Keras, TensorFlow, Python Scikit - Advanced analytical and business strategy skills - Effective communication and presentation skills - Project and process management abilities - Experience in financial services analytics - Strong organizational and multitasking skills - Self-starter with a collaborative team spirit Education: - Bachelors/University degree or equivalent experience, Masters degree preferred In this role, you will be part of the Decision Management job family, focusing on Specialized Analytics (Data Science/Computational Statistics) on a full-time basis. If you require accommodation due to a disability, review the Accessibility at Citi guidelines. For information on Citi's EEO Policy Statement and Know Your Rights, refer to the provided resources.,

You will be joining KPMG in India, a professional services firm affiliated with KPMG International Limited since its establishment in August 1993. Leveraging a global network of firms, we provide services to national and international clients across various sectors with offices in multiple cities across India. As part of the Financial Crimes specialist team, your role will involve providing solutions to BFSI clients through model validation testing for AML risk models and frameworks, sanctions screening, and transaction monitoring systems. We are seeking individuals with advanced data science and analytics skills to support our team in addressing the challenges associated with financial crime. Your responsibilities will include but are not limited to supporting functional SME teams in building data-driven Financial Crimes solutions, conducting statistical testing of screening matching algorithms and risk rating models, validating data models of AML systems, and developing AML models to detect suspicious activities and transactions. You will collaborate with cross-functional teams to analyze data for model development and validation, prepare detailed documentation and reports, and assist in feature engineering for automation of AML-related investigations. To qualify for this role, you should have a Bachelor's degree from an accredited university, at least 3 years of hands-on experience in Python with knowledge of frameworks like Java, Fast, Django, Tornado, or Flask, experience with Relational and NoSQL databases, proficiency in BI tools such as Power BI and Tableau, and an educational background in Data Science and Statistics. Additionally, expertise in machine learning algorithms, statistical analysis, and familiarity with regulatory guidelines for AML compliance are essential. Preferred qualifications include experience in AML model validation, statistical testing of risk models, and familiarity with AML technology platforms. Hands-on experience with data analytics tools like Informatica and Kafka is also desirable. If you are looking to contribute your advanced analytics skills to combat financial crime and support leading financial institutions in adhering to industry best practices, this role offers you the opportunity to work on challenging projects and develop professionally in a dynamic environment.,

As a member of the R&A COE team at EY, you will be part of a dynamic group working on various Data Science and Machine Learning projects. Your role will involve utilizing your experience in data science projects and demonstrating advanced programming skills in SAS, R, or Python. You will be expected to independently understand and address data science problems using techniques such as linear regression, logistic regression, random forest, support vector machines, ANOVA/ANCOVA, time series modeling, segmentation, decision tree, clustering, recommendation engines, and forecasting. In this position, you will collaborate with a diverse team to contribute to Decision Sciences implementation projects. Your responsibilities will include developing analytical strategies for businesses, communicating with onsite coordinators, and presenting model results to clients. Timely completion of assigned tasks and regular status reporting will be essential components of your role. To be successful in this role, you should hold a degree in BE/BTech/MCA/MBA/CA with 0-3 years of experience in Information Management/Analytics. Having an understanding of Business Intelligence & Data Visualization concepts and experience with BI/Visualization tools will be advantageous. Additionally, you should possess excellent communication skills, a collaborative mindset, and a familiarity with software development best practices. If you have a background in the Banking/Finance domain, prior experience in client-facing roles, and strong written and verbal communication skills, it will be considered as additional assets. By joining EY, you will be part of a global organization dedicated to building a better working world through innovation, collaboration, and a commitment to creating value for clients, society, and the planet.,

You will be responsible for building and interpreting machine learning models on real business data from the SigView platform, such as Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees. Your tasks will include identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data. Moreover, you will be expected to extract data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping. Your role will involve validating third-party metrics by cross-referencing various syndicated data sources and determining the numerical variables to be used in the same form as they are from the raw datasets, categorized into buckets, and used to create new calculated numerical variables. You will perform exploratory data analysis using PySpark to finalize the list of compulsory variables necessary to solve the business problem and transform formulated problems into implementation plans for experiments by applying appropriate data science methods, algorithms, and tools. Additionally, you will work with offshore teams post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights. Your responsibilities will also include collating the results of the models, preparing detailed technical reports showcasing how the models can be used and modified for different scenarios in the future to develop predictive insights. You will develop multiple reports to facilitate the generation of various business scenarios and provide features for users to generate scenarios. Furthermore, you will be interpreting the results of tests and analyses to develop insights into formulated problems within the business/customer context and provide guidance on risks and limitations. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite will be crucial for success in this role. This position may involve telecommuting and requires 10% travel nationally to meet with clients. The minimum requirements for this role include a Bachelor's Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years of progressive experience in the job offered or related occupation. Special skill requirements for this role include applying statistical methods to validate results and support strategic decisions, building and interpreting advanced machine learning models, using various tools such as Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation, integrating diverse data sources using data analytics techniques, and performing data analysis and predictive model development using AI/ML algorithms. Your mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra, and Geometry will be beneficial. Familiarity with Data Science libraries such as NumPy, SciPy, and Pandas, Azure Data Factory for data pipeline design, NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT will also be advantageous. The base salary for this position ranges from $171,000 to $190,000 per annum for 40 hours per week, Monday to Friday. If you have any applications, comments, or questions regarding the job opportunity described, please contact Piyush Khemka, VP, Business Operations, at 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310.,

The Economic Analyst, North America (NAM) position at Mastercard Economics Institute (MEI) involves engaging in data analytics and economic research for the U.S. and Canada. Reporting to the VP, Lead Economist for North America at MEI, you will be responsible for supporting client and stakeholder engagements, collaborating with external clients and partners, and generating initial insights to create impactful storylines and visuals. You will also be involved in synthesizing analyses into clear recommendations, writing reports and client presentations, enhancing existing products, and proactively seeking new knowledge to improve productivity. The role requires a Bachelor's degree in Economics, Statistics, or Mathematics, with experience in statistical modeling, quantitative analysis, and R development, focusing on economic research. Proficiency in SQL and Hadoop is essential, along with expertise in R, Python, or other statistical packages. Experience with Tableau is preferred, and knowledge of JavaScript for data visualization is a plus. Familiarity with econometric and statistical techniques such as predictive modeling, regression analysis, time series modeling, and data mining methods is necessary. A willingness to learn additional statistical applications and software is expected. Candidates with prior experience in the financial services industry will be given preference. Strong communication and writing skills are essential for this role, along with the ability to actively participate in thought leadership activities and contribute to the continuous improvement of quality and productivity within the organization.,

As a Senior Data Scientist in the Global Data Science & Advanced Analytics team at Colgate-Palmolive, your role will involve leading projects within the Analytics Continuum. You will be responsible for conceptualizing and developing machine learning, predictive modeling, simulations, and optimization solutions to address business questions with clear dollar objectives. Your work will have a significant impact on revenue growth management, price elasticity, promotion analytics, and marketing mix modeling. Your responsibilities will include: - Conceptualizing and building predictive modeling solutions to address business use cases - Applying machine learning and AI algorithms to develop scalable solutions for business deployment - Developing end-to-end business solutions from data extraction to statistical modeling - Conducting model validations and continuous improvement of algorithms - Deploying models using Airflow and Docker on Google Cloud Platforms - Leading pricing, promotion, and marketing mix initiatives from scoping to delivery - Studying large datasets to discover trends and patterns - Presenting insights in a clear and interpretable manner to business teams - Developing visualizations using frameworks like Looker, PyDash, Flask, PlotLy, and streamlit - Collaborating closely with business partners across different geographies To qualify for this position, you should have: - A degree in Computer Science, Information Technology, Business Analytics, Data Science, Economics, or Statistics - 5+ years of experience in building statistical models and deriving insights - Proficiency in Python and SQL for coding and statistical modeling - Hands-on experience with statistical models such as linear regression, random forest, SVM, logistic regression, clustering, and Bayesian regression - Knowledge of GitHub, Airflow, and visualization frameworks - Understanding of Google Cloud and related services like Kubernetes and Cloud Build Preferred qualifications include experience with revenue growth management, pricing, marketing mix models, and third-party data. Knowledge of machine learning techniques and Google Cloud products will be advantageous for this role. Colgate-Palmolive is committed to fostering an inclusive environment where diversity is valued, and every individual is treated with respect. As an Equal Opportunity Employer, we encourage applications from candidates with diverse backgrounds and perspectives. If you require accommodation during the application process due to a disability, please complete the request form provided. Join us in building a brighter, healthier future for all.,

The Balance Sheet Management Analyst is a seasoned professional role responsible for applying in-depth disciplinary knowledge to contribute to the development of new methodologies, data processing, visualization and analysis tools, and the improvement of processes and workflows for the Balance Sheet Management function. The Balance Sheet Management modeling group within the treasury team is crucial for developing statistical and non-statistical methodologies that directly impact Citigroup's Capital. This team's work is subject to heightened regulatory focus and scrutiny, focusing on the development of models and tools for Deposit duration, Fund Transfer Pricing, Customer Pricing, and other areas used in the IRRBB and treasury space. Key responsibilities of the Analyst include end-to-end development support of statistical models covering asset classes like Deposits or Fixed Income Securities, as well as specific functions such as Asset Allocation strategy. The Analyst is expected to demonstrate analytical/statistical skills, strong communication skills for documenting and presenting work, and stakeholder management abilities to understand requirements and develop suitable models. For non-statistical modeling projects, the Analyst should showcase good analytical skills to filter, prioritize, and validate complex material from multiple sources. The detailed responsibilities involve end-to-end development and governance of models in the treasury/IRRBB space, including econometric forecasting models for key Balance sheet and income statement line items. The Analyst applies analytical thinking, statistical knowledge, and attention to detail when making judgments and analytical recommendations based on data analysis. Model governance and support include timely submission of model documentations to stakeholders. Qualifications and other Requirements: - 2-4 years of relevant statistical modeling/econometrics experience in the financial domain. - PG/Masters/PhD in quantitative disciplines such as Statistics, Economics, Mathematics, or related fields preferred. - Experience in Time Series modeling and development of models and metrics related to ALM/IRRBB. - Hands-on experience with statistical techniques such as Linear Regression, Logistic Regression, Time Series, and more. - Working knowledge of Artificial Intelligence/Machine Learning techniques and programming skills in Python. - Experience with SQL, databases, and programming languages like SAS/R. - Domain knowledge in PPNR, Fixed Income Securities, Mortgage Modeling, and other financial concepts. - Demonstrated analytical skills and ability to synthesize quantitative and qualitative data to support decision-making. - Ability to manage multiple projects and deadlines effectively. This is a full-time position based in Mumbai at a C10 job level within the Finance Job Family Group under Non-Trading Market Risk Management.,

Roles & Responsibilities : Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. Good knowledge of advanced statistical methods. Mine and analyze data, applying statistical methods as necessary, pertaining to customers discovery, and viewing experiences to identify critical product insights. Experience in creating statistical models and/or optimization frameworks for improving processes/products/profits Interact with our research team and with key partners in the market to build end-to-end AI/ML/NLP solutions: Conversational AI, document understanding Mine and analyze data, applying statistical methods as necessary, pertaining to customers discovery, and viewing experiences to identify critical product insights. Proactively develop new metrics and studies to quantify the value of different aspects of product. Drive efforts to enable product and engineering leaders to share your knowledge and insights through clear and concise communication, education, and data visualization. Translate analytic insights into concrete, actionable recommendations for business or product improvement. Build and improve reusable tools & modelling pipelines and support knowledge sharing across several teams. Define and deploy best practices in Machine Learning & MLOps, mentor and teach colleagues. Partner closely with product and engineering leaders throughout the lifecycle of project Education and Work Experience Requirements: 5 to 8 years of experience as Data Scientist Proven track record and experience with statistical modeling/data mining algorithms such as Multivariate Regression, Logistic Regression, clustering algorithms, Support Vector Machines, Decision Trees etc Machine learning, deep learning, graph mining. DOE, Forecasting, Segmentation, Uncertainty Analysis etc. Data Mining i. e. Text Mining, Classification Methods SVM, NN, etc Vector Space model for Unstructured Text Sentiment Analysis, Association Mining, Semantic Analysis Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model Experience in creating statistical models and/or optimization frameworks for improving processes/products/profits Expertise with one of the following scripting languages: Python, R, Tensorflow, Keras, Pytorch OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs Good and experience of machine learning algorithms and ability to apply them in supervised and un-supervised NLP tasks. Knowledge of NLP algorithms that can handle various NLP tasks such as intent recognition, entity extraction, language modeling, text classification, question answering, text summarization, topic modeling and so on. Experience building and fine-tuning Language Models (LMs), such as BERT, ELMo, XLNet etc to solve bespoke NLP tasks. Tech savy and willing to work with open-Source Tools Should have independently handled a project technically and provided directions to the other Team Members. Able to lead the project independently. Experience in turning ideas into actionable designs. Able to persuade stakeholders and champion effective techniques through development. Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company. Good to have foundational knowledge on Cloud, API frameworks like Flask, Fast API Prior experience working on Mobility or Healthcare domain will be a plus

We are seeking an experienced Advanced Analytics Specialist to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background and a passion for transforming complex data into actionable insights. Job Description: Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelor s or Master s degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 3+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc. ) for various objectives Hyper parameter tuning Prompt Engineering Embedding & Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. What We Offer: Opportunities for professional development and career growth. A collaborative and innovative work environment. If you are passionate about data analytics and want to make a significant impact in the retail/CPG industry, we encourage you to apply! Location: Bangalore Brand: Merkle Time Type: Full time Contract Type: Permanent