883 Statistical Modeling Jobs

Your responsibilities include leading a team of 10+ associates to support key deliverables for Region Europe, promoting a data-driven decision-making culture through coaching, mentoring, and introducing industry best practices and external perspectives. You will conceptualize, design, and develop advanced analytics projects and proof of concepts on prioritized use cases incorporating multiple data sources. Additionally, you will design and implement automated data workflows for complex datasets, collaborating with business and IT teams to expand automation and integrate it with existing systems. Your role will involve overseeing data integration across multiple teams to ensure insights are aligned with business priorities and performance objectives. Collaboration with cross-functional global teams to ensure accurate delivery of key projects is also a key aspect of your responsibilities. You will provide thought leadership to foster a culture of data-driven decision-making, identify best practices across the organization and industry, and provide inputs to the team and the broader community. Your role will involve driving data-driven innovation and supporting operational excellence through simplification and automation initiatives. To be successful in this role, you will need a Master's or bachelor's degree in Data Analytics, Data Science, Business, or Engineering; an MBA from a reputed institute is preferred. You should have 10+ years of experience in Data Analytics or related fields, with specific experience in producing insights for senior management and building statistical models to address business issues. Experience in Commercial Analytics in the Pharma or Life Sciences industry is preferred. Additionally, you should have experience working with large datasets, data visualization tools, statistical software packages, and platforms, specifically Python, advanced SQL, Snowflake, AWS, Databricks, PowerBI, and Alteryx. Demonstrated experience in designing and delivering insights using statistical models, AI/ML, including GenAI, is a significant plus. Experience deploying predictive models, user-centric dashboards, cloud-based ELT pipelines, simulation, and optimization models is also a significant plus. Proficiency in project management tools and practices, as well as high proficiency in MS-Excel and PPT, is required. In this role, you will receive benefits such as flexible working arrangements, learning and development opportunities, and more. Join Sandoz, a leader in the Generic and Biosimilar medicines sector, where you can contribute to touching the lives of millions of patients worldwide. Shape the future of Sandoz by leveraging new development capabilities, state-of-the-art production sites, acquisitions, and partnerships to increase access to low-cost, high-quality medicines sustainably. Experience an open, collaborative culture driven by talented and ambitious colleagues, where diversity is welcomed, and personal growth is encouraged. Embrace an agile and collegiate environment with impactful, flexible-hybrid career opportunities. The future is in your hands at Sandoz!,

Embark on a transformative journey as a Quant Analyst at Barclays, where you will spearhead the evolution of the digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. Design analytics and modelling solutions to complex business problems using your domain expertise. Collaborate with technology to specify any dependencies required for analytical solutions, such as data, development environments, and tools. Develop high-performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams. Implement analytics and models in accurate, stable, well-tested software and work with technology to operationalize them. Essential skillsets required for this role include: - A bachelor's or master's degree in computer science or related fields - Strong Computer Science fundamentals - Experience or master's degree in software development, covering the complete Software Development Life Cycle (SDLC), with a strong understanding of software design patterns - Experience or master's degree in Python development - Experience with DevOps tools such as Git, Bitbucket, and TeamCity - Proficiency in technical documentation - Excellent verbal and written communication skills Some other highly valued skills may include: - Experience in a financial institution delivering analytical solutions and model implementation - Experience with Model deployment frameworks and workflows (e.g., databricks, kedro) - Experience in developing frameworks for mathematical, statistical, and machine learning models and analytics used in business decision-making You may be assessed on essential skills relevant to succeed in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology, as well as job-specific technical skills. This role is based out of the Noida location. Purpose of the role: To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. Accountabilities: - Design analytics and modelling solutions to complex business problems using domain expertise - Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments, and tools - Development of high-performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams - Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalize them - Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users - Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy - Ensure all development activities are undertaken within the defined control environment Analyst Expectations: - Perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement - Requires in-depth technical knowledge and experience in their assigned area of expertise - Thorough understanding of the underlying principles and concepts within the area of expertise - Lead and supervise a team, guiding and supporting professional development, allocating work requirements, and coordinating team resources - Impact the work of related teams within the area - Partner with other functions and business areas - Take responsibility for end results of a team's operational processing and activities - Escalate breaches of policies/procedure appropriately - Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to - Demonstrate understanding of how own sub-function integrates with function, alongside knowledge of the organization's products, services, and processes within the function - Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents - Guide and persuade team members and communicate complex/sensitive information - Act as a contact point for stakeholders outside of the immediate function, while building a network of contacts outside the team and external to the organization All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

Are you seeking an exciting opportunity to become a part of a dynamic and expanding team within a fast-paced and challenging environment As a Quant Modelling Associate within our Risk Management and Compliance team at JPMorgan Chase, you will have a crucial role in upholding the strength and resilience of the organization. Your main responsibilities will involve anticipating emerging risks and utilizing your expertise to address challenges that impact the company, its customers, and the communities it serves. You will be an integral part of the Model Risk Governance and Review (MRGR) team, which is accountable for conducting independent model reviews and governance activities to effectively manage Model Risk. Specifically, MRGR Trading focuses on valuation and risk-management models utilized within the Corporate & Investment Bank, with a particular emphasis on Derivatives Instruments that involve complex and advanced modeling techniques. Your key responsibilities will include: Model Review: - Assessing the conceptual soundness of model specifications, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability of performance metrics and risk measures. - Conducting independent testing of models by replicating or creating benchmark models. - Designing and executing experiments to evaluate the potential impact of model limitations, parameter estimation errors, and deviations from model assumptions; comparing model outputs with empirical evidence or outputs from model benchmarks. - Documenting the findings of the model review and effectively communicating them to stakeholders. Model Governance: - Acting as the primary point of contact for model governance-related queries within the coverage area and facilitating the identification and escalation of issues to ensure timely and effective resolutions. - Providing guidance on the proper usage of models to model developers, users, and other stakeholders within the firm. - Staying informed about the ongoing performance testing results for models utilized in the coverage area and communicating these outcomes to stakeholders. - Maintaining the model inventory and model metadata for the coverage area. - Keeping abreast of the latest developments within the coverage area in terms of products, markets, models, risk management practices, and industry standards. Required qualifications, capabilities, and skills: - PhD or Masters degree in a quantitative discipline such as Math, Physics, Engineering, Computer Science, Economics, or Finance. - Proficiency in probability theory, stochastic processes, statistical/economic modeling, partial differential equations, and numerical analysis. - Understanding of options and derivative pricing theory and risks. - Proficient in Python, R, Matlab, C++, or other programming languages. - Possess a risk and control mindset with the ability to ask insightful questions, assess the significance of model issues, and escalate them appropriately. - Strong communication skills enabling effective interaction with front office traders and other functional areas within the firm on model-related matters; capable of producing documents for internal and external (regulatory) purposes. - Strong analytical and problem-solving abilities.,

Job Description: As a leader at a Fortune Global 500 organization, you will be responsible for advocating various data science teams on best practices surrounding the development and implementation of advanced analytic systems and predictive and prescriptive models. Working closely with a team of data scientists, data analysts, data engineers, machine learning engineers, business and data domain owners, application developers, and architects, you will play a crucial role in creating and delivering insights from large and disparate data to enable confident business decisions. Your role will involve evaluating and adopting emerging technologies that support statistical modeling, machine learning, distributed computing, and run-time performance tuning to optimize processes and introduce new products and services to the market. Additionally, you will support senior leadership by planning and executing broad advanced analytics initiatives aimed at delivering value to both internal and external stakeholders. Furthermore, you may also be involved in managing people within the department. Responsibilities: - Lead and oversee the data analysts, data scientist team, machine learning engineers, and big data specialists to implement models and systems that provide optimal results and are scalable to meet future business needs. - Serve as a subject matter expert on UPS business processes, data, and advanced analytics capabilities to define problems, data, and model requirements using proven predictive and prescriptive techniques. - Maintain a broad understanding of implementation, integration, and inter-connectivity issues with emerging technologies to develop strategies that support the creation, development, and delivery of analytic solutions aligned with business needs. - Prototype algorithms to ensure analytic results address problem statements and business requirements effectively. - Interpret and analyze large-scale datasets to uncover insights supporting the building of analytic systems and predictive models while experimenting with new and emerging techniques. - Identify and evaluate cutting-edge open-source, data science/machine learning libraries, data platforms, and vendor solutions to prioritize and plan data projects across the enterprise. - Provide thought leadership, technical guidance, and counsel for data science project teams to evaluate strategic alternatives, recommend courses of action, and design and implement solutions. - Advocate for best practices in the adoption of Cloud-AI technologies, open-source software, machine learning libraries/packages, and data science platforms to derive actionable insights empowering business decisions. - Communicate effectively with business customers and the senior leadership team with varying levels of technical knowledge, educate them about systems, and share insights and recommendations to inform business strategies. - Manage analytics projects/teams and act as a point of contact to ensure alignment of team actions and communication with stakeholders to keep projects on track with goals. Qualifications: - Ability to engage key business and executive-level stakeholders to translate business problems into high-level analytics solutions. - Extensive experience working with large-scale, complex datasets to develop machine learning, predictive, forecasting, and optimization models. - Proven track record of handling ambiguity, prioritizing needs, and delivering results in a dynamic environment. - Expertise in data management pipelines involving data extraction, analysis, and transformation using data querying languages (e.g. SQL, NoSQL, BQ) or scripting languages (e.g. Python, R) and/or statistical/mathematical software (e.g. R, Matlab, SAS). - Hands-on experience in launching moderate to large-scale advanced analytics projects in production at scale; utilizing Cloud-AI technologies, machine learning frameworks, and enterprise data science platforms. - Ability to explain technical concepts to non-experts, strong analytical skills, attention to detail. - Direct experience in developing analytical solutions empowering business decisions and product creation using various techniques (e.g. Supervised, Unsupervised, Deep Learning, NLP). - Excellent verbal and written communication skills with the ability to convey data through a story framework, present data-driven results to technical and non-technical audiences, and advocate technical solutions to diverse groups. - Master's Degree in a quantitative field such as mathematics, computer science, physics, economics, engineering, statistics, or equivalent job experience. Employee Type: Permanent UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.,

The job involves driving strategic initiatives to enhance operational efficiency within the engineering service department. You will collaborate with cross-functional teams to analyze and interpret data for decision-making purposes. Your role will also include developing and implementing data models, databases, data collection systems, and other strategies to optimize statistical efficiency and data quality. Identifying trends and generating insights to drive key business recommendations will be a key aspect of your responsibilities. Additionally, you will provide leadership in data analysis and process improvement within the engineering service department. You will assist in preparing and delivering technical presentations to stakeholders to communicate analytical findings and recommendations. It is essential to stay updated on industry best practices and technological advancements to suggest improvements within the team. As a part of your responsibilities, you will lead strategic projects aimed at enhancing operational productivity within the engineering service department. Working collaboratively with various teams to analyze and derive actionable insights from data will be a crucial aspect of your role. You will design and implement data models and databases to enhance statistical efficiency, identify patterns and trends in data to make informed business decisions, and offer guidance on data analysis methodologies and process enhancements. Presenting analytical findings and recommendations through technical presentations will also be a part of your day-to-day tasks. To qualify for this role, you should hold a Bachelor's degree in Engineering, Computer Science, Data Science, or a related field. You must have proven experience in data analysis, statistical modeling, and interpretation within an engineering setting. Strong proficiency in data visualization tools and techniques is required. Excellent communication skills are essential, with the ability to convey complex data insights effectively. Leadership capabilities to drive initiatives and provide guidance in a team environment are also expected. Familiarity with industry-specific tools and technologies for data analysis and process optimization will be beneficial for this position.,

Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow - people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level. This position involves developing batch and real-time data pipelines utilizing various data analytics processing frameworks in support of Data Science and Machine Learning practices. You will assist in integrating data from various sources, both internal and external, performing extract, transform, load (ETL) data conversions, and facilitating data cleansing and enrichment. Additionally, you will be involved in full systems life cycle management activities, including analysis, technical requirements, design, coding, testing, and implementation of systems and applications software. The role also entails synthesizing disparate data sources to create reusable and reproducible data assets, as well as assisting the Data Science community in analytical model feature tuning. Responsibilities include contributing to data engineering projects and building solutions by leveraging foundational knowledge in software/application development, programming languages for statistical modeling and analysis, data warehousing, and Cloud solutions. You will collaborate effectively, produce data engineering documentation, gather requirements, organize data, and define project scopes. Data analysis and presentation of findings to stakeholders to support business needs will be part of your tasks. Additionally, you will participate in the integration of data for data engineering projects, understand and utilize analytic reporting tools and technologies, and assist with data engineering maintenance and support. Defining data interconnections between operational and business functions, backup and recovery, and utilizing technology solutions for POC analysis are also key responsibilities. Requirements for this role include understanding of database systems and data warehousing solutions, data life cycle stages, data environment scalability, data security, regulations, and compliance. You should be familiar with analytics reporting technologies, algorithms, data structures, Cloud services platforms, ETL tools capabilities, Machine learning algorithms, building data APIs, and coding using programming languages for statistical analysis and modeling. Basic knowledge of distributed systems and a Bachelor's degree in MIS, mathematics, statistics, computer science, or equivalent job experience are necessary qualifications. This is a permanent position at UPS, committed to providing a workplace free of discrimination, harassment, and retaliation.,

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate, and advance faster than ever. As a Micron Front End Central Quality Senior Engineer, you will be a member of the worldwide quality team responsible for driving quality and reliability improvement initiatives into Front End Manufacturing network. You will work closely with Global Quality and internal customers to perform data analysis in key metrics to monitor quality and reliability health, including DPM and Uncorrectable Error (UE) metrics. Additionally, you will work with business partners to develop the strategy for continually improving product quality and reliability for Front End and supporting Time to Mature DPM program and Time to Mature Uncorrectable Error (UE) program execution. Responsibilities And Tasks Include But Not Limited To: - Design and develop methods to extract and analyze unstructured diverse Backend & Front-end data. Perform data correlations to determine the Patterns and perform the first level of debug. - Translate raw data into compelling visual stories that highlight trends, anomalies, and opportunities for improvement. - Collaborate with business partners and multi-functional teams to drive detection, Corrective and Preventive Actions in line-of-sight metrics. - Work with multi-functional team to deploy BKMs of Back End to Front End collaboration process like WL DPM forecast and RMA DPM reduction, etc. - Lead multi-functional initiatives or enabling projects that support companywide quality objectives. - Manage the projects to enable the implementation path for new initiatives. - Strong verbal and written communication skills, able to communicate the analysis and present insights to business partners. Skills And Experience You Will Need: - MS/BS or equivalent experience in Electrical or Computer Engineering. - 3 to 8 years of experience in the following areas. - Good knowledge in Semiconductor Manufacturing, common semiconductor reliability tests, and failure mechanisms. - Fluency in Python and/or R, other statistical software including scripting capability for automating analyses. - Knowledge of using statistical tools, Unix, Tableau, Power BI, JMP. - Understanding of statistics applied to data analysis, especially in Quality and reliability. - Exposure to statistical modeling, feature extraction and analysis. Good to have - supervised/unsupervised/semi-supervised learning, integrating LLM into the production environment. About Micron Technology, Inc.: Micron Technology, Inc. is an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron and Crucial brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.,

As a Data Science Manager, you will have the following key accountabilities: Team Leadership: You will be responsible for building and leading a high-performing team of 6-8 Data Scientists and Machine Learning Engineers in our Pune hub. Your role involves fostering a collaborative and inclusive team culture that encourages innovation and continuous learning. Technical Communication: It is essential for you to effectively explain Data Science principles, concepts, algorithms, and approaches in simple terms to diverse audiences, including non-technical stakeholders. Business Understanding: Your solid business understanding will be utilized to align with stakeholders, discuss requirements and feasibility, and manage expectations effectively. You should ensure clear communication and understanding of project goals and outcomes. Key Qualifications: Educational Background: A PhD or Masters degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, with a minimum of 8+ years of experience as a Data Scientist is required. Leadership Experience: You should have proven experience as a people manager and/or mentor, with a track record of developing and leading high-performing teams. Communication Skills: You must possess the ability to effectively communicate complex methodologies and technologies to both technical and non-technical audiences. Strong problem-solving skills and an independent working style are also essential. Technical Expertise: Your role requires strong statistical and machine learning modeling skills, including statistical tests, classification, predictive modeling, handling of missing data, and sampling/weighting techniques. Proficiency in analytical programming languages such as Python or R, along with their respective ecosystems, is necessary. Hands-on experience implementing these models in production systems and software development skills, including unit testing, CI/CD, and version control with Git are essential. Familiarity with computer science and engineering fundamentals such as data structures, software design principles, and testing strategies is also expected. Preferred qualifications: Experience in the Media industry is a plus. Experience working with cloud-based data services (AWS, Azure, or GCP) is advantageous. Experience with Optimization techniques such as linear programming, integer programming, genetic algorithms, constrained optimization is a plus.,

As a Senior Data Scientist specializing in Artificial Intelligence and Machine Learning at FIS, you will be part of a dynamic team that thrives on curiosity, motivation, and forward-thinking. Your role will involve utilizing cutting-edge AI technologies to tackle complex challenges in the financial services and technology sectors. You will be responsible for leveraging AIML concepts such as GenAI, LLMs, and Sentiment analysis to develop innovative solutions. This will involve establishing correlations between various data points and conducting predictive and preventive analyses to drive business outcomes. Working closely with our AIOPS team, you will contribute to the development of AIML solutions aimed at reducing Enterprise MTTR through a top-notch product. Your day-to-day tasks will include employing machine learning and statistical modeling techniques to enhance data-driven products, extracting actionable insights from diverse datasets, and transforming complex data into actionable information. To excel in this role, you should possess 4 to 6 years of experience in machine learning, artificial intelligence, statistical modeling, and data analysis. Proficiency in data science tools and programming languages such as SAS, Python, R, Scala, and SQL is essential. A relevant degree in Artificial Intelligence Machine Learning, as well as knowledge of cloud-based technologies and the financial services industry, will be advantageous. In return, FIS offers a comprehensive range of benefits to support your wellbeing and lifestyle. You will be part of a diverse and innovative team operating in a modern international work environment. Additionally, you will have access to professional education and personal development opportunities to further enhance your skills and career growth. Join us at FIS and be part of a team that values collaboration, entrepreneurship, and fun while making a meaningful impact in the world of AI and data science.,

You are a Data Scientist with a strong expertise in data analysis, machine learning, and visualization. Your proficiency lies in Python, Pandas, and Matplotlib, and you excel at building and optimizing data-driven models. If you have some experience in Natural Language Processing (NLP) and Named Entity Recognition (NER) models, it would be considered a plus. Your responsibilities include analyzing and processing large datasets using Python and Pandas, developing and optimizing machine learning models for predictive analytics, creating data visualizations using Matplotlib and Seaborn to support decision-making, performing data cleaning, feature engineering, and statistical analysis, working with structured and unstructured data to extract meaningful insights, and implementing and fine-tuning NER models for specific use cases, if required. You will collaborate with cross-functional teams to drive data-driven solutions. To excel in this role, you should have proficiency in Python and data science libraries such as Pandas, NumPy, and Scikit-learn. Experience in data analysis, statistical modeling, and machine learning is essential. Hands-on expertise in data visualization using Matplotlib and Seaborn, along with an understanding of SQL and database querying, is required. Familiarity with NLP techniques and NER models will be an added advantage. Strong problem-solving and analytical skills are essential to succeed in this position.,

The Data Science Associate role at CRM Asia based in Bengaluru involves supporting the data science team in developing, implementing, and maintaining data-driven solutions that align with business objectives. Your duties include working with large datasets, creating data models, and analyzing data to offer insights and recommendations. You will collaborate with the data science team to address business needs through data-driven solutions. This will involve collecting, cleaning, and preprocessing large and complex datasets from various sources. Additionally, you will develop statistical models and predictive models to identify patterns and trends in data and analyze data to discover insights for business enhancement. Furthermore, you will communicate your findings and recommendations to key stakeholders in a clear and concise manner. Data visualization tools will be utilized to present complex data in an easily understandable format. It is essential to stay updated on industry trends and advancements in data science. Qualifications for this role include a Bachelor's or Master's degree in computer science, statistics, mathematics, or a related field. Proficiency in programming languages such as Python or R, experience with data manipulation tools like SQL and Excel, and knowledge of statistical modeling and machine learning techniques are required. Familiarity with data visualization tools such as Tableau or Power BI, excellent problem-solving skills, and strong communication and collaboration abilities are also necessary. For this position, proficiency in at least one programming language like Python, R, or SQL is essential. A solid understanding of statistics and mathematics is crucial, including knowledge of probability theory, statistical inference, and basic linear algebra. Data wrangling skills involving cleaning, transforming, and merging data, as well as knowledge of machine learning concepts and data visualization tools, are important requirements. Communication skills are key for explaining findings to stakeholders, and problem-solving skills are needed to identify and frame problems in a data-driven manner. It is vital to be aware of potential fraudulent job offers and understand that Capillary Technologies does not extend unsolicited employment offers or request fees from prospective employees during the recruitment process. CRM Asia is committed to an inclusive recruitment process and equality of opportunity for all job applicants.,

As an intern at Underpin Services, you will have the opportunity to collaborate with game designers and developers in designing, analyzing, and refining game mechanics and systems using mathematical models. Your responsibilities will include assisting in the creation of simulations and statistical models to predict and analyze game outcomes. You will be expected to perform data analysis to identify trends and insights that can directly inform game design decisions. Additionally, you will work on the mathematical aspects of random number generation (RNG) and probability distributions in games. Your input in providing feedback and suggestions on game features and mechanics from a mathematical perspective will be highly valued. It is crucial to stay up-to-date with industry trends and best practices in game mathematics and apply them effectively to ongoing projects. Underpin Services is a digital marketing consultancy and branding services company that prides itself as a trusted partner for businesses looking to thrive in the digital landscape. Join our dedicated team of experts who specialize in delivering tailored digital agency services to empower small businesses.,

As a Demand Planning Manager, you will be responsible for developing and implementing a global demand planning strategy that aligns with the supply chain objectives of the organization. Your key responsibilities will include designing, implementing, and refining standard demand planning processes, tools, and systems. You will also provide guidance and support to regional planning teams by offering training, sharing best practices, and building their capabilities. In this role, you will collaborate with various functions such as sales, marketing, finance, IT, and supply chain to ensure that demand forecasts are accurate and actionable. You will lead demand planning initiatives like scenario planning, demand sensing, and predictive analytics. Additionally, you will integrate planning processes with digital tools and promote the adoption of AI-driven solutions. Furthermore, you will work closely with global and regional planning leads to align processes and technology across different markets. Your proactive approach will involve identifying integration challenges between tools and processes to ensure smooth system adoption. You will also be responsible for monitoring key planning metrics, including forecast accuracy and inventory performance, and driving continuous improvements in these areas. To be successful in this role, you should have 7-10 years of experience in demand planning or related supply chain roles. You must possess a strong understanding of forecasting techniques, statistical modeling, and planning processes. Proficiency in tools such as SAP IBP, Kinaxis, o9, or similar platforms is essential, and familiarity with Blue Yonder will be considered a plus. Your ability to lead cross-functional initiatives and work effectively in matrixed environments will be crucial. Demonstrated success in implementing advanced planning technologies and enhancing planning maturity will also be valuable. A B.Tech degree along with a management degree from a Tier 1 B school are the required qualifications for this role. If you are looking for a challenging opportunity to drive global demand planning strategies and make significant contributions to the supply chain function of the organization, this role could be the perfect fit for you.,

As a Mathematical, Statistical, and Machine Learning Modeler at our organization, your role is vital in designing, developing, implementing, and supporting models and analytics that drive key business decisions. Your responsibilities include: Designing analytics and modeling solutions to address complex business challenges by leveraging your domain expertise. Collaborating with technology teams to define necessary dependencies for analytical solutions, including data, development environments, and tools. Developing highly effective, well-documented analytics and modeling solutions, showcasing their impact to business users and independent validation teams. Implementing models and analytics in reliable, well-tested software and working with technology partners to ensure their operational success. Providing continuous support to maintain the effectiveness of analytics and modeling solutions for end-users. Ensuring adherence to all Barclays Enterprise Risk Management Policies, particularly the Model Risk Policy, and conducting all development activities within the established control framework. In this role, you are expected to manage a significant business function, contributing to strategic initiatives, policy development, and complex projects. You will lead a large team or sub-function, fostering a performance-driven culture and aligning with the organization's values. Alternatively, as an individual contributor, you will lead projects across the organization, serving as a technical expert and thought leader, driving innovation and collaboration. Your responsibilities also include providing expert advice to senior management, overseeing resourcing and budgeting, managing policy creation, and ensuring compliance with regulations. You will monitor external environments, regulators, and advocacy groups to advocate on behalf of Barclays when necessary. Additionally, you are required to maintain in-depth knowledge of industry practices, market trends, and business integration to achieve overall objectives. As a Senior Leader, you must exhibit the Barclays leadership behaviours: Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others. Furthermore, you are expected to embody the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as the Barclays Mindset of Empower, Challenge, and Drive. Your role as a Mathematical, Statistical, and Machine Learning Modeler is crucial in driving data-driven decisions and ensuring the organizations success through innovative and effective analytics solutions.,

The ideal candidate will be responsible for managing all HR activities and operations within the organization. This includes overseeing recruitment, onboarding, employee relations, performance management, and compliance with HR policies and procedures. Additionally, the candidate will be expected to develop and implement HR strategies to support the organization's goals and objectives. Key responsibilities include: - Developing and implementing HR policies and procedures. - Managing the recruitment process from sourcing to onboarding. - Overseeing employee relations and ensuring a positive work environment. - Conducting performance management evaluations and providing feedback to employees. - Managing and resolving employee conflicts and issues. - Providing guidance and support to managers on HR-related matters. - Ensuring compliance with all relevant employment laws and regulations. Qualifications: - Bachelor's degree in HR or related field. - 3-5 years of HR experience. - Strong knowledge of HR best practices and employment laws. - Excellent communication and interpersonal skills. - Ability to work effectively in a fast-paced environment. Interested candidates can share their updated resume at @.,

Embark on a transformative journey as a Quant Analyst at Barclays, where you will spearhead the evolution of the digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. Design analytics and modeling solutions to complex business problems using domain expertise. Collaborate with technology to specify any dependencies required for analytical solutions, such as data, development environments, and tools. Develop high-performing, comprehensively documented analytics and modeling solutions, demonstrating their efficacy to business users and independent validation teams. Implement analytics and models in accurate, stable, well-tested software and work with technology to operationalize them. Essential skillsets required for this role include: - A bachelor's or master's degree in computer science or related fields - Strong Computer Science fundamentals - Experience or Master's degree in software development, covering the complete Software Development Life Cycle (SDLC), with a strong understanding of software design patterns - Experience or Master's degree in Python development - Experience with DevOps tools such as Git, Bitbucket, and TeamCity - Proficiency in technical documentation - Excellent verbal and written communication skills Some other highly valued skills may include: - Experience in a financial institution delivering analytical solutions and model implementation - Experience with Model deployment frameworks and workflows (e.g., databricks, kedro) a plus - Experience in developing frameworks for mathematical, statistical, and machine learning models and analytics used in business decision-making You may be assessed on essential skills relevant to succeed in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology, as well as job-specific technical skills. This role is based out of the Noida location. Purpose of the role: To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. Accountabilities: - Design analytics and modeling solutions to complex business problems using domain expertise - Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments, and tools - Development of high-performing, comprehensively documented analytics and modeling solutions, demonstrating their efficacy to business users and independent validation teams - Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalize them - Provision of ongoing support for the continued effectiveness of analytics and modeling solutions to users - Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy - Ensure all development activities are undertaken within the defined control environment Analyst Expectations: - Perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement - Requires in-depth technical knowledge and experience in their assigned area of expertise - Thorough understanding of the underlying principles and concepts within the area of expertise - Lead and supervise a team, guiding and supporting professional development, allocating work requirements, and coordinating team resources - Impact the work of related teams within the area - Partner with other functions and business areas - Take responsibility for end results of a team's operational processing and activities - Escalate breaches of policies/procedure appropriately - Take ownership for embedding new policies/procedures adopted due to risk mitigation - Advise and influence decision making within the own area of expertise - Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to - Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organization's products, services, and processes within the function All colleagues are expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They are also expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

About the Role: We are seeking a motivated and talented Derivatives Analyst Intern to join our team. In this role, you will learn and apply options theory, contribute to the development of trading strategies, and play a pivotal role in building and maintaining automated trading systems. This is an excellent opportunity to bridge theoretical knowledge with practical applications in a dynamic trading environment. Key Responsibilities: Master the Fundamentals: Learn and apply options theory while gaining an in-depth understanding of our business operations and trading systems. Build & Innovate: Develop and maintain advanced business intelligence and trading tools to drive decision-making. Optimize Performance: Monitor and enhance strategy performance in real-time for maximum efficiency and profitability. Engineer Automation: Design and implement automated trading systems and position management algorithms. Refine Pricing Models: Work on enhancing valuation models to ensure accuracy and profitability. Code & Innovate: Build, maintain, and improve the companys codebase and technology stack. Requirements: Educational Background: A Bachelors degree (or working toward one) in STEM, Statistics, Econometrics, or Quantitative Finance. Passion for Markets : A strong interest in options trading and financial markets, demonstrated through courses, projects, or prior experience. Result-Oriented Mindset: A proven ability to prioritize and deliver results in a fast-paced environment. Problem-Solving Skills: The ability to apply theoretical knowledge to solve practical challenges effectively. Technical Proficiency: Experience in Python is a valuable asset, or a strong desire to master it. Adaptability: Agility to excel in a fast-changing, high-stakes trading environment. Excellent Communication Skills: Strong verbal and written English skills to articulate complex ideas clearly. Preferred Skills: Familiarity with statistical modeling and data analysis tools. Exposure to algorithmic trading concepts and technologies. Knowledge of financial derivatives and their valuation techniques. Who Should Apply: Students or recent graduates with a strong foundation in quantitative disciplines. Individuals passionate about financial markets and trading. Self-starters who are eager to learn, grow, and contribute to a fast-paced team environment. Benefits: Competitive stipend. Real-world experience in derivatives trading and quantitative analysis. Flexible working hours and exposure to cutting-edge technologies. Opportunity for a full-time role based on performance. Show more Show less

As a Senior Data Scientist, you will lead data-driven projects and play a key role in shaping the data science strategy of the organization. Your responsibilities will include developing advanced algorithms, managing large-scale datasets, and providing mentorship to junior team members. You will design and implement complex statistical models and machine learning algorithms, ensuring high-quality deliverables from project conception to deployment. Additionally, you will guide junior data scientists, collaborate with business stakeholders to define project objectives, and deliver actionable insights. To be successful in this role, you should hold a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. With at least 5 years of experience in data science, you must demonstrate a proven track record of leading successful projects. Deep understanding of advanced machine learning techniques, including deep learning and ensemble methods, is essential. Proficiency in programming languages like Python or R, experience with big data technologies (e.g., Apache Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP), and advanced data visualization skills are required. Moreover, you should possess excellent problem-solving and analytical skills with a strategic mindset. Strong communication and leadership skills are crucial for effectively influencing stakeholders at all levels. You will be expected to present findings to executive leadership and recommend data-driven strategies for business growth. In terms of business needs, you should be able to meet with different levels of management, understand industry-specific use cases, and handle clients across multiple industries simultaneously. Additionally, you must have the capability to create dashboards and build stories for top management presentations based on data insights.,

Responsible for Global HR reporting & Analytics in the organization. Compile HR data and metrics from the human resource information system and payroll outputs Responsible for data management, analytical & HR systems support to various stakeholders. Required Candidate profile Minimum 3 years of experience in MIS / Data Analytics. Experience in data management, analytical, & HR systems. Strong data analytical & problem-solving skills. Proficient with Microsoft Excel & PPT.

At our company we are leveraging analytics and technology, as we invent for life on behalf of patients around the world. We are seeking those who have a passion for using data, analytics, and insights to drive decision making, that will allow us to tackle some of the world's greatest health threats. Within our commercial Insights, Analytics, and Data organization we are transforming to better power decision-making across our end-to-end commercialization process, from business development to late lifecycle management. As we endeavor, we are seeking a dynamic talent to be a founder and serve in the role of Manager Data Science. Primary Responsibilities: Conduct comprehensive analysis to measure marketing performance using advanced statistical techniques and marketing mix modelling and optimize promotional investment Partner with cross-functional teams to gather and organize data from multiple sources, ensuring data accuracy and completeness. Use organization and industry information to identify trends, assess current business practices and results, and/or evaluate specific function/operation changes and anticipate their impact Identify KPIs to evaluate marketing performance and provide actionable insights to optimize marketing strategies and budgets. Effectively articulate the business findings with stakeholders Develop and maintain regular analytics deliverables and meet quality standards by following best practices, timeliness, compliance, and excellent user experience. Mentor the junior members of the team to maintain execution excellence Proactively build effective working relationships with those who have the knowledge, experience, resources or influence advance work goals. Have an agile mindset of continuous learning and focus on integrating enterprise value into team culture Collaborate with other members in team to create and present compelling, easy-to-understand data visualization and data driven insights for analytics leaders from the U.S. and Ex-US markets Qualifications Education & Work Experience Requirements: Master's degree (relevant field like Economics, Statistics, Mathematics, Operational Research) with 4 to 7 years work experience Bachelor's degree (in Engineering or related field, such as Computer Science, Data Science, Statistics, Business, etc.) with at least 5-7 years relevant experience Work Experience in the Pharma industry will be preferred Skillset: Candidates must have: Strong programming skills in languages such as Python or R, with experience in data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, statsmodels) Proficiency in SQL for data extraction and manipulation from databases Knowledge of statistical modelling techniques such as linear regression, logistic regression, decision trees, and clustering Good understanding of MS Excel and PowerPoint Strong problem solving, business analysis and quantitative skills Ability to effectively communicate analysis insights to business stakeholders Exposure to agile framework & project management Candidates are desired but not mandatory to have: Marketing Mix Model experience Experience with real world data (e.g., claims, electronic health records) Familiarity with both structured and unstructured data Experience with data science principles and machine learning algorithms (supervised and unsupervised), test-control analysis, propensity score matching etc. Understanding of other tools like Tableau, PowerBI, Dataiku etc.

You will join Salesforce, a company that aims to inspire the future of business through the integration of AI, data, and CRM. Upholding core values, Salesforce empowers companies across various industries to innovate and engage with customers in unique ways. As a member of the team, you will have the opportunity to become a Trailblazer, enhancing your performance, advancing your career, and contributing to positive change in the world. As an experienced Data Scientist, your primary responsibility will be to develop marketing attribution, causal inference, and uplift models to enhance the efficiency and effectiveness of marketing initiatives. This role will involve designing experiments and ensuring a consistent approach to experimentation and campaign measurement across marketing, customer engagement, and digital use cases. The ideal candidate will possess extensive experience in creating statistical models and AI/ML algorithms for marketing and digital optimization on large-scale datasets within a cloud environment. Rigorous testing and evaluation of algorithm performance will be essential, both during development and in production. Moreover, a deep understanding of statistical and machine learning techniques is necessary, along with a commitment to the ethical use of data in algorithm design. Key Responsibilities: - Develop statistical and machine learning models to enhance marketing effectiveness, including attribution models, causal inference models, and uplift models. - Create optimization and simulation algorithms to optimize marketing spend across channels and improve ROI. - Lead the entire model development lifecycle from ideation to deployment, monitoring, and tuning. - Design experiments to support marketing, customer experience, and digital campaigns, and collaborate with peers to establish consistent experimentation and measurement approaches. - Cultivate strong cross-functional relationships and collaborate with key partners throughout the organization. - Stay updated on innovations in enterprise SaaS, AdTech, paid media, data science, customer data, and analytics fields. Required Skills: - 8+ years of experience in designing models for marketing optimization using statistical and machine learning techniques. - Proficiency in developing advanced statistical techniques for experiment design and causal inference methods. - Expertise in programming languages such as Python, R, PySpark, Java, and SQL. - Experience with cloud platforms like GCP and AWS for model development and deployment is preferred. - Strong quantitative reasoning skills and the ability to provide data-driven business insights. - Excellent written and verbal communication skills with a collaborative mindset. - Ability to simplify complex problems and a creative approach to finding solutions. - B2B customer data experience and knowledge of Salesforce products are advantageous.,

Description We are looking for an experienced Seed Technology professional to join our team in India. The ideal candidate will have a strong background in seed research and development, with a focus on improving seed quality and yield. This role requires a combination of technical expertise, analytical skills, and the ability to work collaboratively with agricultural stakeholders. Responsibilities Conduct research and development in seed technology. Evaluate seed quality and performance through field trials and laboratory analysis. Collaborate with agronomists and plant breeders to develop superior seed varieties. Stay updated with the latest advancements in seed technology and agricultural practices. Provide technical support and training to farmers and agricultural stakeholders. Analyze data and prepare reports on seed performance and market trends. Skills and Qualifications 6-16 years of experience in seed technology or related field. Strong understanding of plant genetics and breeding techniques. Familiarity with seed production processes and quality assurance standards. Proficient in data analysis software and statistical tools. Excellent communication and interpersonal skills for collaboration with diverse teams. Ability to conduct field trials and interpret agronomic data.

You will be responsible for developing and optimizing AI/ML models using Python across various applications. Your role will involve conducting Research & Development (R&D) to implement cutting-edge AI methodologies and working with Large Language Models (LLMs) for NLP, text generation, and conversational AI applications. It will also include applying Predictive Analysis techniques to derive data-driven insights and enhance decision-making processes. Collaboration with cross-functional teams to integrate AI solutions seamlessly into business processes is a key aspect of this role. Additionally, staying updated with the latest advancements in AI and ML to improve model performance is crucial. To excel in this position, you must possess a strong proficiency in Python and its AI/ML libraries such as TensorFlow, PyTorch, and Scikit-learn. Previous experience in Research & Development (R&D) for AI and machine learning applications is highly desirable. Hands-on experience with Large Language Models (LLMs) like GPT, BERT, or similar architectures is essential. Expertise in Predictive Analysis, which includes statistical modeling and machine learning techniques, will be a significant part of your responsibilities. Strong problem-solving skills and the ability to work effectively with large datasets are essential. Knowledge of cloud platforms like AWS, GCP, or Azure would be advantageous. The ideal candidate should hold a Masters or Ph.D. in Computer Science, AI, Data Science, or a related field. Experience with MLOps, model deployment, and API integration is preferred. Familiarity with data visualization tools and frameworks will be an added advantage. With 6-8 years of experience, your primary skill set should revolve around AI/ML Development, with additional expertise in TensorFlow and NLP.,

As a technical data analyst intern, you will utilize data analysis and statistical skills on various supply chain projects and activities. You will work in a dynamic environment and be responsible for a wide range of predictive analytics, statistical applications, and modeling. Your main tasks will involve automating and streamlining data gathering and reporting methodologies. Your contributions will play a vital role in enhancing the productivity and effectiveness of Vyrian's sales teams, ultimately leading to increased revenue and margin. To be eligible for this internship, you should be pursuing a Bachelor's of Science or Master's degree in any math, science, or engineering field. Strong math and statistical modeling skills are required, with a preference for those majoring in Statistics or Data Science. Proficiency in SQL, BI tools, and Excel is necessary to produce ad-hoc data analyses and presentations. Additionally, knowledge in advanced analytics tools such as Python, R, Einstein Plus, and Dataiku would be advantageous. If you love working with large volumes of data and are proactive in your approach to work with minimal supervision and high motivation, you are a good fit for this role. Strong reasoning abilities, sound judgment, organizational skills, and the ability to prioritize tasks are also key qualities that we are looking for in potential candidates. We appreciate all applicants for submitting their qualifications. However, only those individuals who are being considered for an interview or are currently employed by Vyrian will be contacted.,

You are an experienced Senior Quantitative Analyst (Model Developer/Validator) with extensive expertise in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your role involves leading the development and validation of advanced credit risk models, including PD, EAD, LGD, with a special emphasis on Expert judgment-based PD models for Corporate, Specialized Lending, and Financial Institutions. Your responsibilities include conducting thorough data preparation and preprocessing using tools such as SAS, Python, R, and SQL. Collaborating with various stakeholders to analyze, interpret, and communicate complex model results and insights is crucial. You are expected to develop detailed technical documentation for regulatory compliance, test plans, validation reports, findings reports, and Business Requirements Documents (BRD) where applicable. Continuous improvement of models is key, which involves identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance and predictive accuracy. Additionally, you will provide mentorship and technical guidance to junior team members to foster a culture of knowledge sharing and professional development. To qualify for this role, you need to have 5-10 years of hands-on experience in credit risk model development and validation, along with proven expertise in modeling across retail and wholesale credit portfolios. Advanced proficiency in SAS, Python, R, and SQL is essential, as well as a deep understanding of IFRS9 and CECL regulatory frameworks and guidance. Excellent analytical and problem-solving skills are required, complemented by strong written and verbal communication abilities. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning, and advanced statistical modeling techniques, as well as knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques.,