36 Julia Jobs - Page 2

About The Position Chevron ENGINE is looking for high-performing Seismic Imaging and Processing Geophysicist candidates to join our Earth Science team. The role provides a wide variety of technical products to support as well as asset teams and research and development activities across the enterprise with a focus on basins with complex seismic imaging problems. Key Responsibilities Delivers key technical geophysical analysis products and interpretation such as: Support and help engineer Chevron's cutting-edge cloud-based FWI seismic imaging technology and workflows Work with assets on seismic imaging problems in complex sub-salt imaging exploration and production assists Tasks will also include performance of routine compliance tasks, automated and manual software compatibility testing for periodic system and software upgrades, and close coordination with Subsurface Platform Systems Engineers Required Qualifications Minimum of MSc degree in STEM field from a deemed/recognized (AICTE) university or equivalent At least 5 years industry related experience Experience with Petrel and seismic software development is a requirement. ML/AI coding skills. C# programing skills or Ocean SDK experience. Familiarity with modern software environments [Microsoft ADO and/or GitHub]. Familiarity with industry seismic processing software packages [e.g. SeisSpace, Reveal, DELFI, Hampson-Russell] Good communication skills and work effectively in a team environment Preferred Qualifications Experience with modern HPC and cloud environments Experience in Julia, Python, C++, Java preferred Experience executing processing and imaging workflows is a differentiator Fundamental knowledge of geophysical workflows applied to subsurface Understanding of physical processes associated with earth science, reservoir modeling and subsurface Chevron ENGINE supports global operations, supporting business requirements across the world. Accordingly, the work hours for employees will be aligned to support business requirements. The standard work week will be Monday to Friday. Working hours are 8:00am to 5:00pm or 1.30pm to 10.30pm. Chevron participates in E-Verify in certain locations as required by law. Show more Show less

Job Description Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It With Pride. You will be crucial in supporting our business by creating valuable, actionable insights about the data, and communicating your findings to the business. You will work with various stakeholders to determine how to use business data for business solutions/insights. How You Will Contribute You will: Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization. In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modeling Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business. After that you will work with stakeholders to determine how to use business data for business solutions/insights Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor results Apply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements What You Will Bring A desire to drive your future and accelerate your career and the following experience and knowledge: Strong quantitative skillset with experience in statistics and linear algebra. A natural inclination toward solving complex problems Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc. Good communication skills to promote cross-team collaboration Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc. Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholders More About This Role You will represent and communicate data requirements to help us understand our data assets and the relationships among them. You will investigate, analyze and scope data requirements to support the development of data integration, data retrieval and reusable data sets. What you need to know about this position: The Data Scientist will be responsible for advanced forecasting methodologies for demand forecasting to generate better forecasting results in terms of accuracy and bias Determine, create and maintain the best Statistical models be to be used by considering SKU demand behavior using segmentation strategy to generate high-quality demand statistical forecast with low forecast error and bias Refine forecasting models by reviewing forecast performance and incorporating feedback from the Demand Planner to improve forecast error and bias metrics Analyze the model performance every month/week where MAPE (Main Absolute Percentage Error) is deteriorating and post process the output and if required finetune the output Propose additional strategies to have a better code (efficient or more accurate) to execute in Databricks. Collaborate with Demand Planners to provide explainability of models and gather feedback to improve the models Lead, develop, and deploy some algorithms built on databricks that help to make the predictive process more efficient and accurate. What extra ingredients you will bring: Lead statistical forecasting process to provide business a statistical base forecast for its demand planning process. Lead some continuous improvement projects to get a more efficient, robust, and accurate models to predict. Analyze business requirements as a guide for data modeling and apply data analysis, design, modeling, and quality assurance techniques, based on a detailed understanding of business processes, to establish, modify or maintain data structures and associated components (entity descriptions, relationship descriptions, attribute definitions Manage the iteration, review and maintenance of data requirements and data models and you will assist in creating the sematic layer of data Choose a suitable data modeling approach for each project, such as by assessing the suitability of existing data models and build data models with the flexibility to change when business requirements change Reconcile multiple logical source models into a single, logically consistent model and you will ensure that the proposed model follows data architecture guidelines and best practices Design, build, implement and/or maintain Python/PySpark algorithms to execute predictive analysis which help to improve planning processes. Analyse code, define and implement strategies to have more accurate and efficient results Education / Certifications: Bachelor's Degree required. Masters in quantitative field of Statistics, Applied Mathematics or Engineering, with specific full-time courses in Analytics preferred Certifications Google Cloud Platform as Data Scientist, or Data Analyst, or in Databricks (nice to have) Experience in any Data Science language like Python (preferred), PySpark (preferred), R, Julia. Experience developing and deploying Statistical and/or machine learning solutions. Knowledge and experience in data science cloud platforms like Databricks (preferred) or similar. +5 years of applied knowledge of analytical techniques in statistical modelling, machine learning with exposure to forecasting domain especially driver-based forecasting Experience on working with FMCG, Food & Beverages, Retail or similar industry data with understanding the business process will be an advantage (nice to have) Should be able to articulate data science outcome into business understandable language Experience leading projects and/or processes Fluent English is a must Job specific requirements: A desire to drive your future and accelerate your career and the following experience and knowledge: Extensive experience in data modeling in a large complex business with multiple systems Ability to simplify complex problems and communicate them to a broad audience Design, build, implement and/or maintain Python/PySpark algorithms to execute predictive analysis which help to improve planning processes. Analyze code, define, and implement strategies to have more accurate and efficient results Working in cloud computing environments with tools like databricks and help MDLZ to have better practices on it. Aligning and coordinating activities with different areas and stakeholder to guarantee a good execution of projects and processes. Travel requirements: Work schedule: Relocation Support Available? Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy Business Unit Summary We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions. If you think the open position you see is right for you, we encourage you to apply! Our people make all the difference in our succes Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. Excited to grow your career? We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions. If you think the open position you see is right for you, we encourage you to apply! IF YOU REQUIRE SUPPORT TO COMPLETE YOUR APPLICATION OR DURING THE INTERVIEW PROCESS, PLEASE CONTACT THE RECRUITER Job Type Regular Data Science Analytics & Data Science Show more Show less

Product Strategy @Dream11 The Product Strategy team is responsible for creating a powerful and focused strategy to drive user engagement and growth. The team works closely with the product & data science teams to solve problems around pricing, profitability & user experience. We tackle these issues by building economic/econometric models, machine learning systems, and high-impact experiments which we integrate into business and system-level decision-making. Your Role: Develop pricing strategies that integrate price elasticity and long-term user retention Design and conduct causal studies using observational and experimental data to drive key business decisions Own and manage the in-game economy to effectively balance liquidity Inform key decisions for fantasy sports experiences to drive retention Qualifiers: PhD in economics, statistics, finance, quantitative marketing, or related fields 4+ years of post-PhD experience in applied economics with exposure to applied microeconometrics, empirical IO, and labor economics, along with experience of applying them to real-world problems Experience in programming languages, such as Python, R & Julia About Dream Sports: Dream Sports is India’s leading sports technology company with 250 million users, housing brands such as Dream11 , the world’s largest fantasy sports platform, FanCode , a premier sports content & commerce platform and DreamSetGo , a sports experiences platform. Dream Sports is based in Mumbai and has a workforce of close to 1,000 ‘Sportans’. Founded in 2008 by Harsh Jain and Bhavit Sheth, Dream Sports’ vision is to ‘Make Sports Better’ for fans through the confluence of sports and technology. For more information: https://dreamsports.group/ Show more Show less

Summary Position Summary Associate Vice President - Quality Engineer Specialist (AI) Role Overview: As a Quality Engineer Specialist Leader specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft and be the visionary driving force behind our transformation to AI-powered quality engineering, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while driving tangible value for Deloitte's business investments. Leveraging your extensive quality engineering and AI craftsmanship, along with advanced proficiency across multiple quality assurance disciplines and modern AI/GenAI frameworks and models, you will consistently demonstrate an exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a strong background in quality assurance, test automation, and a deep understanding of AI and GenAI technologies, including their application to quality engineering. This role is crucial in enhancing our testing frameworks and ensuring the highest quality standards for our products. The team US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Responsibilities: Strategic Vision and Alignment: Accountable for crafting and articulating a vision for AI/GenAI as it specifically applies to quality engineering in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams across various organizational levels. Advocacy and Technology Roadmap: Advocate for, develop, and communicate the AI/GenAI quality engineering implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress. Focus on reuse and leverage of existing quality assets to minimize overall costs with an eye on continuous improvement. Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs related to quality approaches, automation tools, test data management (e.g., subsetting, masking, generation, virtualization, anonymization), and standards, ensuring they are fit-for-purpose in product testing cycles. Implement advanced techniques such as BDD and GenAI-based automation to evolve testing frameworks and increase automation coverage, minimizing manual quality assurance to exceptional scenarios only. Establish and refine AI/ML/GenAI domain standards and best practices. Remain hands-on with test design and scripting/coding automations, contributing to team velocity during sprints, and actively engage with engineers across the SSDLC. Be self-driven to learn new technologies, experiment with them, and inspire quality engineers to apply new technologies effectively. Capability Evolution and Development: Mentor and develop quality engineers to become masters of their craft. Coach and develop their skills in modern engineering practices, specifically related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations with academia and communities. Iterative Value Delivery: Embrace an iterative/incremental approach to quality engineering. Apply a leaning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence. Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement. Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering and quality engineering practices. Identify inefficiencies and opportunities for innovation. Act as a role model and enhance the product engineering operating model to be lean, adaptable, and responsive to changes, ensuring that quality engineering teams can deliver business value efficiently and effectively. Guide and transform the organization to embrace lean principles and foster a culture of innovation. Tech/Quality Risk Management: Ensure appropriate quality tool use, adoption by quality engineers, and confirm/review that products are tested, scaled, and operated to be free of defects and are secure/compliant, including providing guidance for necessary optimizations. Identify potential quality risks and develop mitigation strategies. This involves proactive problem-solving and contingency planning to address any issues that may arise during development. Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence. Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization, from team members to middle management to executives. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels. Key Qualifications: A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 15+ years of hands-on experience in quality assurance/engineering, test automation including coding the test scripts, and in AI/ML, with last 2 years focused on GenAI as well. Proven experience in Python, TensorFlow, PyTorch, Keras, C#, Julia, and ML libraries. Strong experience in GenAI models and technologies such as OpenAI, Claude, Gemini, LangChain, Vector databases, and approaches like prompt engineering, fine-tuning, etc. Hands-on experience with automation-first techniques like BDD and test automation tools such as TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ. Strong experience with cloud hyper-scalers like AWS, Azure, and GCP. Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, and deployment techniques like Blue-Green, and Canary to enable A/B testing approaches. Proven track record of leading and managing high-performing quality engineering teams. Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 302376 Show more Show less

Summary Position Summary Associate Vice President - Quality Engineer Specialist (AI) Role Overview: As a Quality Engineer Specialist Leader specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft and be the visionary driving force behind our transformation to AI-powered quality engineering, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while driving tangible value for Deloitte's business investments. Leveraging your extensive quality engineering and AI craftsmanship, along with advanced proficiency across multiple quality assurance disciplines and modern AI/GenAI frameworks and models, you will consistently demonstrate an exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a strong background in quality assurance, test automation, and a deep understanding of AI and GenAI technologies, including their application to quality engineering. This role is crucial in enhancing our testing frameworks and ensuring the highest quality standards for our products. The team US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Responsibilities: Strategic Vision and Alignment: Accountable for crafting and articulating a vision for AI/GenAI as it specifically applies to quality engineering in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams across various organizational levels. Advocacy and Technology Roadmap: Advocate for, develop, and communicate the AI/GenAI quality engineering implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress. Focus on reuse and leverage of existing quality assets to minimize overall costs with an eye on continuous improvement. Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs related to quality approaches, automation tools, test data management (e.g., subsetting, masking, generation, virtualization, anonymization), and standards, ensuring they are fit-for-purpose in product testing cycles. Implement advanced techniques such as BDD and GenAI-based automation to evolve testing frameworks and increase automation coverage, minimizing manual quality assurance to exceptional scenarios only. Establish and refine AI/ML/GenAI domain standards and best practices. Remain hands-on with test design and scripting/coding automations, contributing to team velocity during sprints, and actively engage with engineers across the SSDLC. Be self-driven to learn new technologies, experiment with them, and inspire quality engineers to apply new technologies effectively. Capability Evolution and Development: Mentor and develop quality engineers to become masters of their craft. Coach and develop their skills in modern engineering practices, specifically related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations with academia and communities. Iterative Value Delivery: Embrace an iterative/incremental approach to quality engineering. Apply a leaning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence. Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement. Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering and quality engineering practices. Identify inefficiencies and opportunities for innovation. Act as a role model and enhance the product engineering operating model to be lean, adaptable, and responsive to changes, ensuring that quality engineering teams can deliver business value efficiently and effectively. Guide and transform the organization to embrace lean principles and foster a culture of innovation. Tech/Quality Risk Management: Ensure appropriate quality tool use, adoption by quality engineers, and confirm/review that products are tested, scaled, and operated to be free of defects and are secure/compliant, including providing guidance for necessary optimizations. Identify potential quality risks and develop mitigation strategies. This involves proactive problem-solving and contingency planning to address any issues that may arise during development. Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence. Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization, from team members to middle management to executives. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels. Key Qualifications: A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 15+ years of hands-on experience in quality assurance/engineering, test automation including coding the test scripts, and in AI/ML, with last 2 years focused on GenAI as well. Proven experience in Python, TensorFlow, PyTorch, Keras, C#, Julia, and ML libraries. Strong experience in GenAI models and technologies such as OpenAI, Claude, Gemini, LangChain, Vector databases, and approaches like prompt engineering, fine-tuning, etc. Hands-on experience with automation-first techniques like BDD and test automation tools such as TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ. Strong experience with cloud hyper-scalers like AWS, Azure, and GCP. Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, and deployment techniques like Blue-Green, and Canary to enable A/B testing approaches. Proven track record of leading and managing high-performing quality engineering teams. Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 302376 Show more Show less

Requisition ID: 93622 Job Category: Engineering Location: Gurugram, Haryana, India Join a company that is passionately committed to the pursuit of a better world through positive change. With more than 65 years of business and technical expertise in mining, energy, and infrastructure, our 10,000 colleagues in 150 countries tirelessly work toward bettering the industries in which we operate. With practical solutions that are safe, innovative and sustainable, we think globally while acting locally. Join our Project Delivery Group (PDG), a dynamic team of professionals passionately committed to world-class project delivery across the globe. With expertise in sustainable studies, asset building and operations, and industry-leading efficiencies, our best-in-class team leverages methodologies, governance and systems that are unparalleled in the engineering space. Are you looking for an opportunity to join a diverse group of professionals who are committed to remaining exceptional? We look forward to hearing from you. The global energy transition is upon us. As we shift to a low carbon world, meeting the growing demand for energy will require revolutionary thinking and a variety of resources. While the market is challenging, these challenges present the biggest opportunities and catalysts for change. The Energy group partners with clients to provide comprehensive plans that incorporate all aspects of their projects. Our energy expertise in the oil and gas sector comprises the entire value chainupstream, midstream, and downstream; and in the power sector includes thermal, nuclear, waterpower, renewable, hybrid, transmission and distribution, and grid modernization. Join our team today and help make a difference! Our team is seeking a Power Systems Planning Engineer . The incumbent of this position is required to work within focused study teams and multi-disciplinary teams involved in integrated power system plans, transmission and distribution system plans, pre-feasibility/feasibility/system impact assessment, and system performance studies for both AC and DC project developments and generation/load connections. They will coordinate all planning activities and those of their teams to maintain project schedules and ensure successful project completion. The person will perform the duties in accordance with all applicable codes and standards, including all of Hatchs policies and procedures, such as Safety, Environmental and Quality Assurance. The incumbent should be familiar with policies, guidelines, regulations, rules, requirements, and criteria as applicable to grid performance, transmission planning, and interconnection, especially to bulk power systems. The position will be based in India, out of the Gurugram office . Responsibilities and Qualifications Requirements: Experience in utility/system operator transmission planning Lead projects and mentor engineers in the performance of transmission planning studies, such as load flow, short-circuit, transient stability, electromagnetic transient, and/or small-signal stability analysis. Lead preparation of comprehensive reports on the conduct of the studies, the study results and appropriate conclusions and recommendations Review of planning/system performance studies for compliance with prevailing standards and criteria and good engineering practice Lead interaction with clients and manage projects. Support business development activities Preparation of functional specifications for facility requirements related to different system development portfolios, for purposes of developing preliminary designs and obtaining estimates for the associated facilities. Undertake thought leadership activities (e.g., speaker at conference, panelist, whitepaper, etc.) and promote Hatch’s know-how in the Power and T&D sector in the region. BS degree in Electrical Engineering; post-graduate (MS or PhD) degrees in Power Systems. At least 5 years of experience in transmission planning with strong knowledge of transmission planning practices and procedures. Proficient in power flow, short-circuit, and transient stability simulation analysis, using software packages such as PSS®E, PSLF, PowerWorld, DSA Tools, etc., including modules for load flow, short-circuit, and transient stability analysis. High level of interpersonal communication skills. Preferred: Proficiency in electromagnetic transients (EMT) analysis using software packages such as PSCAD, EMTP-RV, etc. Knowledge of control theory, dynamic modeling, and numerical methods. Knowledge of programming languages such as Python, C, C++, FORTRAN, MATLAB, Julia, etc. Experience with Simulink is preferred. Knowledge of additional power systems analysis software applications is desirable. Registration with IEEE, CIGRE, and/or other applicable engineering associations is desirable. Why join us? Work with great people to make a difference Collaborate on exciting projects to develop innovative solutions Top employer What we offer you? Flexible work environment Long term career development Think globally, work locally Don't meet every single requirement? You don't need to. At Hatch, we are building a diverse, inclusive workplace that fosters innovation. If you're interested in this role, we encourage you to apply even if your past experiences don't perfectly align with the skills we've listed. We're committed to fostering a workforce that reflects the diversity of the communities in which we operate and serve. Hatch is an Equal Opportunity Employer that considers applicants without regard to age, race, color, national origin, citizenship, religion, creed, gender, sexual orientation, marital status, disability, veteran, or any other protected status. If you have any accommodation requirements, please let us know. We'll do our best to meet your needs in accordance with applicable local legislation.

Skill required: Delivery - Digital Marketing Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Any Graduation Years of Experience: 7 to 11 years What would you do? Data & AIIn digital marketing analytics, you will be involved in processes and technologies that enable marketers to effectively evaluate the success and value of their digital marketing initiatives, identify trends and patterns over time and make data driven decisions. What are we looking for? Data Science Proficiency in Data Modeling, Experimental Design/Analysis, Marketing and/or Business Analytics. Knowledge of Data Science and Machine Learning concepts and algorithms. Experienced with programming languages and Data Science scripting (in Python / R / Scala / Julia) Experience with Cloud Technologies Experience in implementing ethical practices into data science. Negotiation skills Problem-solving skills Adaptable and flexible Results orientation Prioritization of workload Roles and Responsibilities: Utilize advanced statistical and machine learning techniques to address complex business problems Possess the ability to conduct exploratory data analysis and present findings in ways that are meaningful to stakeholders Develop, refine, and implement models that enhance decision-making processes. Perform comprehensive preprocessing of both structured and unstructured data to ensure its quality and relevance Undertake data collection, analysis, and interpretation to extract meaningful insights. Analyze vast datasets to identify trends, patterns, and correlations that contribute to informed decision-making Build, refine, and deploy predictive models and machine-learning algorithms that align with business objectives Collaborate closely with engineering and marketing teams to understand their requirements and integrate data-driven solutions into their workflows Conduct ad-hoc analyses to provide timely and relevant insights, along with actionable recommendations to address pressing business questions Develop and implement machine learning solutions, including audience segmentation, marketing engagement level evaluation, and prioritization of sales engagement with accounts Manage the end-to-end lifecycle of machine learning models, including training, testing, deployment, and continuous improvement Effectively communicate complex findings and insights to both technical and non-technical stakeholders Document methodologies, data sources, and models to ensure transparency and reproducibility Qualifications Any Graduation

Job Profile Conduct research on various aspects of electric mobility, including battery technology, charging infrastructure, and vehicle-to-grid integration. Perform simulation & experimentation to assess the impacts of EV integration in distribution systems. Prepare technical reports, research papers, and presentations to disseminate findings. Experience 0 - 2 Years Qualification Graduate/Post Graduate Degree in Electrical/Electronics/Power Engineering or a related field. Prior experience in the power or renewable energy sector is a preferred. Skills - Proficiency in programming languages such as Python- MATLAB- or Julia. Familiarity with power system modelling software e.g. DIgSILENT PowerFactory or similar. Ability to work on hardware and simulation platforms. Strong skills in Excel and Power-BI for data analysis and reporting. Excellent communication and writing abilities. Location Delhi Salary As per norms Please apply latest by May 15, 2025

Job Profile The candidate will work on projects related to energy transition, renewable energy integration, smart grid technologies and electric vehicle (EV) technologies. The candidate is expected to lead and support junior team members by providing technical assistance and knowledge transfer. The candidate must have strong understanding of the following domains: 1. Electric Mobility: EV technologies, including battery management systems (BMS), electric drivetrains, and charging infrastructure, EV policies, regulations, and market trends, Vehicle-to-Grid (V2G) concepts. 2. Electricity Distribution Sector & Smart Grid Technologies: Strong understanding of electricity distribution systems operation. Experience with integrating Distributed Energy Resources (DER) and EVs into the distribution network, understanding of regulatory frameworks and policies governing the electricity distribution sector and smart grid implementation. 3. Energy Storage Solutions: Analyzing the economic feasibility and performance metrics of energy storage solutions (Battery Energy Storage Systems (BESS), Solar with BESS). Experience 0 - 5 Years Qualification - Ph.D. or equivalent degree in Electrical/Electronics/Power Engineering or having 4 years of research- design & development experience after ME/M.Tech. in Electrical/Electronics/Power/Renewable Engineering or a related field. Skills - Proficiency in programming languages such as Python- MATLAB- or Julia. Proficiency with power system modelling software e.g. DIgSILENT PowerFactory or any other. Hands-on experience on hardware and simulation platforms. Strong skills in Excel and Power-BI for data analysis and reporting. Excellent communication and writing abilities. Location Delhi Salary As per norms Please apply latest by May 15, 2025

Skill required: Delivery - Digital Marketing Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Any Graduation Years of Experience: 7 to 11 years What would you do? Data & AIIn digital marketing analytics, you will be involved in processes and technologies that enable marketers to effectively evaluate the success and value of their digital marketing initiatives, identify trends and patterns over time and make data driven decisions. What are we looking for? Data Science Proficiency in Data Modeling, Experimental Design/Analysis, Marketing and/or Business Analytics. Knowledge of Data Science and Machine Learning concepts and algorithms. Experienced with programming languages and Data Science scripting (in Python / R / Scala / Julia) Experience with Cloud Technologies Experience in implementing ethical practices into data science. Negotiation skills Problem-solving skills Adaptable and flexible Results orientation Prioritization of workload Roles and Responsibilities: Utilize advanced statistical and machine learning techniques to address complex business problems Possess the ability to conduct exploratory data analysis and present findings in ways that are meaningful to stakeholders Develop, refine, and implement models that enhance decision-making processes. Perform comprehensive preprocessing of both structured and unstructured data to ensure its quality and relevance Undertake data collection, analysis, and interpretation to extract meaningful insights. Analyze vast datasets to identify trends, patterns, and correlations that contribute to informed decision-making Build, refine, and deploy predictive models and machine-learning algorithms that align with business objectives Collaborate closely with engineering and marketing teams to understand their requirements and integrate data-driven solutions into their workflows Conduct ad-hoc analyses to provide timely and relevant insights, along with actionable recommendations to address pressing business questions Develop and implement machine learning solutions, including audience segmentation, marketing engagement level evaluation, and prioritization of sales engagement with accounts Manage the end-to-end lifecycle of machine learning models, including training, testing, deployment, and continuous improvement Effectively communicate complex findings and insights to both technical and non-technical stakeholders Document methodologies, data sources, and models to ensure transparency and reproducibility Qualifications Any Graduation

Skill required: Delivery - Digital Marketing Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Any Graduation Years of Experience: 7 to 11 years What would you do? Data & AIIn digital marketing analytics, you will be involved in processes and technologies that enable marketers to effectively evaluate the success and value of their digital marketing initiatives, identify trends and patterns over time and make data driven decisions. What are we looking for? Data Science Proficiency in Data Modeling, Experimental Design/Analysis, Marketing and/or Business Analytics. Knowledge of Data Science and Machine Learning concepts and algorithms. Experienced with programming languages and Data Science scripting (in Python / R / Scala / Julia) Experience with Cloud Technologies Experience in implementing ethical practices into data science. Negotiation skills Problem-solving skills Adaptable and flexible Results orientation Prioritization of workload Roles and Responsibilities: Utilize advanced statistical and machine learning techniques to address complex business problems Possess the ability to conduct exploratory data analysis and present findings in ways that are meaningful to stakeholders Develop, refine, and implement models that enhance decision-making processes. Perform comprehensive preprocessing of both structured and unstructured data to ensure its quality and relevance Undertake data collection, analysis, and interpretation to extract meaningful insights. Analyze vast datasets to identify trends, patterns, and correlations that contribute to informed decision-making Build, refine, and deploy predictive models and machine-learning algorithms that align with business objectives Collaborate closely with engineering and marketing teams to understand their requirements and integrate data-driven solutions into their workflows Conduct ad-hoc analyses to provide timely and relevant insights, along with actionable recommendations to address pressing business questions Develop and implement machine learning solutions, including audience segmentation, marketing engagement level evaluation, and prioritization of sales engagement with accounts Manage the end-to-end lifecycle of machine learning models, including training, testing, deployment, and continuous improvement Effectively communicate complex findings and insights to both technical and non-technical stakeholders Document methodologies, data sources, and models to ensure transparency and reproducibility Qualifications Any Graduation