Role Description We are looking for a DevOps Engineer to develop and support integrated automation solutions.Thisindividualwillworkinateamsetting,workingtocreate&maintainCI/CD pipelines,troubleshoot,enhance&manageoursoftwaredeliverypipelines,manageour cloudinfrastructureandcreatetoolingtostreamlineandenhancethecurrentautomation workflows and help build new workflows for next generation solutions. Responsibilities BethemainpointofcontactforourteamforCloudandInfrastructure management Develop, enhance and manage deployment automation pipelines implementing DevOps best practices Manage cloud infrastructure platforms Identify the scope of enhancements to our infrastructure and automation pipelines Assist in automating in-house processes Configuration Management for Cloud based infrastructure Manage and design deployment processes implementing cloud infrastructure security Requirements Requirements: Candidate with a well-rounded experience as a DevOps engineer Experience in software development for cloud-based applications and container-based solutions (Docker, Docker Swarm, Kubernetes) Computer Science degree or relevant experience in Software Development Experience handling large data sets Cloud management experience (primarily AWS and Azure) Setup and management of databases (MySQL, PostgreSQL), database services, virtual machines, virtual networks, IAM policies ComfortablewithVCS–GitHuband GitOps Experience in software development preferably in Java and Python preferred Experience in using Linux systems and bash scripting Experience in automating software deployments across environments using CI/CD pipelines. Experience working together with teams from several departments Understanding of best practices regarding system architecture, design, security, throughput, availability and scalability Show more Show less
Role Description WearelookingforaDevOpsEngineertodevelopandsupportintegratedautomation solutions.Thisindividualwillworkinateamsetting,workingtocreate&maintainCI/CD pipelines,troubleshoot,enhance&manageoursoftwaredeliverypipelines,manageour cloudinfrastructureandcreatetoolingtostreamlineandenhancethecurrentautomation workflowsandhelpbuildnewworkflowsfornextgenerationsolutions. Responsibilities BethemainpointofcontactforourteamforCloudandInfrastructure management Develop,enhanceandmanagedeploymentautomationpipelines implementing Implement and manage DevOpsbest practices Manage and configurecloudinfrastructure platforms/solutions Identify the scope of enhancements to our infrastructure and automation pipelines and implement them Assistinautomatingin-house processes Configuration Management for Cloud based infrastructure Manageanddesigndeploymentprocessesimplementingcloudinfrastructure security Requirements Requirements: 4+yearsofwell-roundedexperienceasaDevOps engineer Experienceinsoftwaredevelopmentforcloud-basedapplicationsand container-based solutions(Docker,DockerSwarm, Kubernetes) ComputerSciencedegreeorrelevantexperiencein the Software Development Life Cycle Experiencehandlinglargedata sets Cloudmanagementexperience(primarilyAWSand Azure) Setupandmanagement ofdatabases and database services (MySQL, PostgreSQL – both managed and unmanaged) , virtualmachines,virtualnetworks,IAM policies, API Gateways. Experience in setting up and managing MLOps and LLMOps pipelines (experience with AWS Bedrock, Langchain, vector databases) ComfortablewithVCS–GitHuband GitOps Experience in software development preferably in Java, Javascript or Python preferred Experiencein managing and usingLinuxsystemsand writing bash scripts Experience in automating software and deployment processes for CI/CD. Experienceworkingtogetherwithteamsfromseveral departments and great communication skills Understandingofbestpracticesregardingsystemarchitecture,design, security, throughput, availability and scalability Show more Show less
Job Title Engineering Lead at GIST Impact, based out of Bengaluru - On-site Role Company Details GIST Impact, based in Nyon, Switzerland, is a leading environmental services company providing impact data and analytics. With over 100 scientific experts, it supports companies and investors globally in measuring and quantifying corporate impacts across markets. Job Roles & Responsibilities - Lead AI/ML engineering projects to enhance GIST Impact's data analytics platforms. - Develop and optimize machine learning models using Python, PyTorch, Scikit-Learn, and TensorFlow. - Collaborate with a multidisciplinary team of scientists, engineers, and data scientists. - Drive innovation in impact data computation and ESG analytics. - Ensure scalability and efficiency in handling large, geographically precise datasets. - Mentor junior engineers and promote best practices in AI/ML development. - Interface with clients and partners to align product features with market needs. - Stay updated on industry trends in AI/ML and environmental services for continuous product improvement. Cultural Expectations - Collaborate effectively with diverse teams of scientists, data scientists, and economists - Communicate complex ideas clearly to technical and non-technical stakeholders - Foster a culture of continuous learning and innovation - Champion sustainable practices and impact-driven solutions - Align projects with GIST Impact’s mission for precise impact measurement - Promote teamwork in a fast-paced, dynamic environment Hiring Process Profile shortlisting Automated coding Tech interview Tech interview Tech interview Tech interview Show more Show less
Role Description We are seeking a detail-oriented and analytical finance professional to join our team, specializing in Management Reporting, Analysis and financial modelling. The ideal candidate will play a critical role in financial data analysis, reporting, and supporting decision-making processes. Proficiency in advanced Excel, data visualization, and presentation skills is essential for success in this role. Job Duties And Responsibilities Finance Transformation & Process Optimization Lead and project manage end-to-end delivery of key finance transformation initiatives across the group. Redesign and implement improvements to core finance processes to enhance automation, control, and scalability. Oversee and drive process improvements through template creations and training across: Month-end close Purchase ledger Order-to-cash Expense management Approval workflows Develop and maintain finance templates, forms, and SOPs. Design, structure and help create the investor data room to support audits, fundraising, and due diligence. Contribute to project-based financial initiatives with a focus on automation and operational efficiency. Standardize and roll out balance sheet reconciliation templates across the group. MIS Reporting & Analysis Design and roll out maintenance of monthly MIS dashboards to monitor financial performance, KPIs, and business metrics. Create the capabilities to analyze and present financial data, including P&L, budgets, forecasts, and variance reports. Project manage and roll out the timeliness of all management reports, dashboards, and presentations. Financial Modeling & Data Management Build and manage integrated financial models for budgeting, forecasting, scenario analysis and variance analysis. Collect, organize, and validate financial and operational data from multiple systems. Ensure data integrity and resolve discrepancies effectively. Presentation & Visualization Prepare clear and compelling templates for presentations using PowerPoint for internal and external stakeholders. Visualize complex data for decision-making using charts, graphs, and dashboards. Collaboration & Stakeholder Management Work closely with finance, operations, and cross-functional teams to enhance data flow and reporting. Support audit processes, reconciliations, and other ad-hoc finance projects. Upskill and train team members to embed best practices and tools. Continuous Improvement Identify opportunities for streamlining reporting processes and automating manual tasks. Stay updated with financial reporting trends, tools, and best practices. Desired Professional Traits Proactive and self-motivated with a strong sense of ownership. Natural problem-solver who can identify process gaps and drive implementation. Collaborative mindset with the ability to work cross-functionally. Clear communicator who can translate complex data into actionable insights. Adaptable, curious, and eager to adopt new tools and best practices. Requirements Required Skills And Experience Master’s degree in Finance, Business Analytics, or a related field. Additional certification or coursework in Sustainability is a strong plus. Proven experience in financial reporting, MIS, and transformation in a scaling or tech environment of minimum 3 years. Advanced proficiency in Microsoft Excel (including pivot tables, formulas, charts, and scenario tools). Strong PowerPoint skills for presentation development. Familiarity with data visualization tools like Tableau , Power BI , or Google Data Studio is advantageous. Familiarity with accounting softwares like Tally, Bexio, Zoho Books, Xero . Excellent analytical, problem-solving, and data interpretation skills. Strong attention to detail and the ability to manage multiple priorities.
Role Description: We are seeking a detail-oriented and analytical finance professional to join our team, specializing in Management Reporting, Analysis and financial modelling. The ideal candidate will play a critical role in financial data analysis, reporting, and supporting decision-making processes. Proficiency in advanced Excel, data visualization, and presentation skills is essential for success in this role. Job Duties and Responsibilities: Finance Transformation & Process Optimization Lead and project manage end-to-end delivery of key finance transformation initiatives across the group. Redesign and implement improvements to core finance processes to enhance automation, control, and scalability. Oversee and drive process improvements through template creations and training across: Month-end close Purchase ledger Order-to-cash Expense management Approval workflows Develop and maintain finance templates, forms, and SOPs. Design, structure and help create the investor data room to support audits, fundraising, and due diligence. Contribute to project-based financial initiatives with a focus on automation and operational efficiency. Standardize and roll out balance sheet reconciliation templates across the group. MIS Reporting & Analysis Design and roll out maintenance of monthly MIS dashboards to monitor financial performance, KPIs, and business metrics. Create the capabilities to analyze and present financial data, including P&L, budgets, forecasts, and variance reports. Project manage and roll out the timeliness of all management reports, dashboards, and presentations. Financial Modeling & Data Management Build and manage integrated financial models for budgeting, forecasting, scenario analysis and variance analysis. Collect, organize, and validate financial and operational data from multiple systems. Ensure data integrity and resolve discrepancies effectively. Presentation & Visualization Prepare clear and compelling templates for presentations using PowerPoint for internal and external stakeholders. Visualize complex data for decision-making using charts, graphs, and dashboards. Collaboration & Stakeholder Management Work closely with finance, operations, and cross-functional teams to enhance data flow and reporting. Support audit processes, reconciliations, and other ad-hoc finance projects. Upskill and train team members to embed best practices and tools. Continuous Improvement Identify opportunities for streamlining reporting processes and automating manual tasks. Stay updated with financial reporting trends, tools, and best practices. Desired Professional Traits: Proactive and self-motivated with a strong sense of ownership. Natural problem-solver who can identify process gaps and drive implementation. Collaborative mindset with the ability to work cross-functionally. Clear communicator who can translate complex data into actionable insights. Adaptable, curious, and eager to adopt new tools and best practices. Required Skills and Experience: Masters degree in Finance, Business Analytics, or a related field. Additional certification or coursework in Sustainability is a strong plus. Proven experience in financial reporting, MIS, and transformation in a scaling or tech environment of minimum 3 years. Advanced proficiency in Microsoft Excel (including pivot tables, formulas, charts, and scenario tools). Strong PowerPoint skills for presentation development. Familiarity with data visualization tools like Tableau , Power BI , or Google Data Studio is advantageous. Familiarity with accounting softwares like Tally, Bexio, Zoho Books, Xero . Excellent analytical, problem-solving, and data interpretation skills. Strong attention to detail and the ability to manage multiple priorities.
Role Description We are hiring a Senior Environmental Data Scientist to lead the technical development of nature and biodiversity data solutions. This is a high-impact individual contributor role for an environmental scientist first and foremost who is additionally an accomplished data scientist and programmer. You’ll be responsible for transforming scientific research into scalable analytics, building robust environmental data products, and supporting product development through direct technical contribution. You will also play a soft leadership role — supporting and mentoring junior data scientists, guiding generalists on environmental matters, and helping shape the long-term data science capacity of the Nature & Biodiversity team. This is a senior-level hire with a clear path to team leadership as our company grows. You will report to the Head of Nature & Biodiversity Products . Job Duties And Responsibilities Lead Development of Data Solutions: Design and implement advanced data pipelines, metrics, and models that assess how businesses interface with nature. Apply Environmental Science at Scale: Translate robust environmental science into analytical workflows that can support business decisions and regulatory needs. Drive Methodological Rigor: Incorporate peer-reviewed methodologies and scientific best practices into product development; stay ahead of innovations in the field. Architect Scalable Data Solutions: Develop performant, production-ready code and collaborate with engineers to build tools for spatial, temporal, and exploratory analysis. Mentor and Guide: Support junior data scientists, serve as the go-to environmental expert across functions, and help build the team’s overall environmental data science capacity. Engage with Frameworks: Apply knowledge of sustainability disclosure and risk frameworks (e.g. TNFD, ESRS, SBTN, SFDR) to develop solutions that meet evolving stakeholder needs. Collaborate and Communicate: Work cross-functionally with product, research, and engineering teams to translate scientific insight into real-world impact. Represent your work with external stakeholders as needed. Requirements Experience, Qualifications And Skills Environmental Expertise: PhD (preferred) or Master’s in environmental science, ecology, conservation, geosciences, or a closely related field. Experience: 5+ years applying data science to environmental or sustainability contexts; experience in a product-oriented or startup environment is a must. Programming & Engineering: Expert Python developer with strong engineering discipline (e.g., Git, unit testing, CI/CD); experience building high-quality analytical code. Geospatial & Remote Sensing: Advanced skills in spatial analysis, GIS tools, and remote sensing data workflows (e.g., raster/vector processing, spatial joins, indexing). Data Science & Machine Learning: Proficiency in statistical modelling, spatial ML, and fundamental AI/ML methods (e.g., scikit-learn, PyTorch, foundation models). Data Systems: Hands-on experience with relational and spatial databases (e.g., PostGIS), cloud data tools (e.g., Snowflake), and handling unstructured and structured data. Framework Fluency: Demonstrated ability to interpret and implement solutions aligned with environmental frameworks such as TNFD, ESRS, SFDR, and SBTN. Communication: Ability to explain complex ideas clearly to both technical and non-technical audiences; experience with data storytelling and visualization is a plus. Team Fit: Collaborative, proactive, impact-driven, and adaptable — comfortable with the fast pace and opportunities of a growing startup. Preferred Qualifications Deep experience with one or more particular nature-related domains, such as: biodiversity impact modeling; physical risk analysis; nature risk valuation. Experience contributing to or leading cross-disciplinary scientific or open-source projects. Work experience at corporate sustainability offices, financial institutions, regulatory bodies, or nature data providers.
Job Duties And Responsibilities Framework Development & Integration Lead the design, enhancement, and implementation of climate risk management frameworks, integrating both physical and transition risks into bank-wide risk processes. Ensure frameworks align with Basel IV, IFRS 9, TCFD, NGFS, and other leading regulatory and industry standards. Risk Identification, Assessment & Modeling Identify, assess, and quantify climate-related risks across credit, market, and operational risk domains. Develop and execute advanced climate scenario analyses and stress tests, leveraging both deterministic and stochastic approaches. Build and validate credit risk models (PD, LGD, EAD) and valuation models for both equity and debt portfolios, incorporating climate risk factors. Apply financial modeling techniques to assess the impact of climate scenarios on balance sheets, P&L, and capital adequacy. Data Science & Analytical Tools Design and deploy sophisticated analytical tools using Python and other programming languages for data manipulation, modeling, and visualization. Integrate AI/ML techniques to enhance predictive accuracy and scenario analysis capabilities. Regulatory Compliance & Stakeholder Engagement Serve as the in-house expert on climate-related financial regulations, ensuring full compliance with global and local requirements. Prepare regulatory submissions, respond to queries, and maintain proactive engagement with regulators. Collaborate with business units (credit, market risk, corporate banking) to embed climate risk into daily decision-making. Reporting, Disclosure & Thought Leadership Oversee the preparation of high-quality internal and external climate risk reports and disclosures for senior management, boards, investors, and regulators. Communicate complex climate risk concepts in a clear, actionable manner to diverse stakeholders. Stay at the forefront of climate science, sustainable finance, and regulatory trends, driving continuous improvement and innovation. Requirements Experience, Qualifications And Skills Experience: Minimum 8 years in climate risk, sustainability, or related roles within financial services or regulatory bodies. Education: PhD or Masters degree in Climate Science, Data Science, Environmental Science, Energy, or related field; OR Masters or equivalent in Actuarial Science, Financial Engineering, Mathematics, or other quantitative disciplines. Technical Expertise: Demonstrable experience in credit risk modeling, valuation modeling (equity and debt), and financial modeling in a banking or investment context. Advanced proficiency in Python for data analysis, modeling, and visualization; experience with other analytical tools (e.g., R, MATLAB, SAS) is a plus. Certifications: GARP (Global Association of Risk Professionals) certifications such as FRM (Financial Risk Manager) are highly desirable. Regulatory Knowledge: Deep familiarity with Basel III/IV, TCFD, NGFS, and other climate risk regulatory frameworks. Analytical Skills: Strong quantitative and analytical capabilities, with proven experience in scenario analysis and stress testing. Communication & Leadership: Excellent written and verbal communication skills; able to convey complex technical concepts to non-technical audiences. Demonstrated ability to lead cross-functional projects, influence stakeholders, and drive organizational change. Other Attributes: Strong problem-solving skills, attention to detail, and ability to work both independently and collaboratively. Show more Show less
Role And Responsibilities Climate Risk Modelling & Scenario Analysis: Lead the development and application of advanced models for assessing physical (e.g., floods, heatwaves) and transition risks (e.g., policy shifts, low-carbon technologies) across sectors and asset classes, using tools like CLIMADA and aligned with NGFS, IPCC, and TCFD frameworks. Environmental & ESG Data Analytics: Design and implement methodologies to model environmental impacts (carbon, water, waste, biodiversity) using large-scale datasets, LCA databases, geospatial data, and remote sensing tools for cross-sectoral risk quantification. Financial Risk Integration: Collaborate with banks and financial institutions to embed climate and ESG risk indicators into credit rating models, stress testing frameworks, underwriting processes, and portfolio risk assessments to meet regulatory and disclosure expectations (e.g., CSRD, PCAF, EU Taxonomy). Research Leadership & Regulatory Alignment: Drive applied research and thought leadership through publications, IP development, and academic collaborations. Ensure climate analytics methodologies stay aligned with evolving standards and frameworks (e.g., ISSB, GFANZ, SBTN). Stakeholder Engagement & Communication: Present technical findings and strategic insights to clients, regulators, and internal teams. Contribute to multi-disciplinary innovation projects involving sustainability experts, data scientists, engineers, and product managers. Requirements Required Skills and Qualifications: Climate & Environmental Risk Expertise: Over 4 years of hands-on experience in climate/environmental risk analysis, with a strong focus on the financial sector including work with banks, asset managers, DFIs, or credit rating agencies. Demonstrated ability to apply or develop risk models tailored to regulatory frameworks such as Basel III/IV, TCFD, NGFS, and IFRS S2. Technical & Analytical Proficiency: Skilled in data science and statistical analysis using Python, R, MATLAB, and Excel. Experienced with climate datasets (e.g., CMIP6, ERA5, WorldClim), geospatial tools (QGIS, ArcGIS), and physical risk modelling frameworks like CLIMADA. Familiar with ESG standards and sustainability data integration. Financial Risk Knowledge: Solid understanding of credit and market risk principles, with the ability to overlay climate and environmental risks into traditional financial risk frameworks. Strong grasp of financial concepts, credit assessment, and stress testing methodologies. Research & Thought Leadership: Demonstrated thought leadership through publications, white papers, or industry contributions at the intersection of climate science, data analytics, and finance. Proven experience working in interdisciplinary teams spanning science, engineering, finance, and technology. Communication & Collaboration: Excellent verbal and written communication skills with a strong command of English. Effective at presenting complex findings to technical and non-technical audiences. Highly collaborative, detail-oriented, self-motivated, and capable of managing work both independently and in team settings. Qualification: Advanced degree (master’s or PhD) in Environmental Science, Nature and Biodiversity related fields, Sustainability, or any related discipline.
Role Description: As a Data Engineering Lead, you will play a crucial role in overseeing the design, development, and maintenance of our organization's data architecture and infrastructure. You will be responsible for designing and developing the architecture for the data platform that ensures the efficient and effective processing of large volumes of data, enabling the business to make informed decisions based on reliable and high-quality data. The ideal candidate will have a strong background in data engineering, excellent leadership skills, and a proven track record of successfully managing complex data projects. Responsibilities: Data Architecture and Design: - Design and implement scalable and efficient data architectures to support the organization's data processing needs - Work closely with cross-functional teams to understand data requirements and ensure that data solutions align with business objectives ETL Development: - Oversee the development of robust ETL processes to extract, transform, and load data from various sources into the data warehouse - Ensure data quality and integrity throughout the ETL process, implementing best practices for data cleansing and validation Big Data Technologies: - Stay abreast of emerging trends and technologies in big data and analytics, and assess their applicability to the organization's data strategy - Implement and optimize big data technologies to process and analyze large datasets efficiently Cloud Integration: - Collaborate with the IT infrastructure team to integrate data engineering solutions with cloud platforms, ensuring scalability, security, and performance Performance Monitoring and Optimization: - Implement monitoring tools and processes to track the performance of data pipelines and proactively address any issues - Optimize data processing workflows for improved efficiency and resource utilization Documentation: - Maintain comprehensive documentation for data engineering processes, data models, and system architecture - Ensure that team members follow documentation standards and best practices. Collaboration and Communication: - Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and deliver solutions that meet those requirements - Communicate effectively with technical and non-technical stakeholders, providing updates on project status, challenges, and opportunities. Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. 6-8 years of professional experience in data engineering In-depth knowledge of data modeling, ETL processes, and data warehousing. In-depth knowledge of building the data warehouse using Snowflake Should have experience in data ingestion, data lakes, data mesh and data governance Must have experience in Python programming Strong understanding of big data technologies and frameworks, such as Hadoop, Spark, and Kafka. Experience with cloud platforms, such as AWS, Azure, or Google Cloud. Familiarity with database systems like SQL, NoSQL, and data pipeline orchestration tools. Excellent problem-solving and analytical skills. Strong communication and interpersonal skills. Proven ability to work collaboratively in a fast-paced, dynamic environment.