Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Scientist, your primary role revolves around leveraging Python and SQL to conduct data science modelling, employing statistical and machine learning algorithms to derive actionable insights. Your responsibilities will encompass: Data Modeling: Developing and implementing sophisticated data science models to extract valuable insights from complex datasets. Algorithm Implementation: Applying statistical and machine learning algorithms to solve business problems and enhance decision-making processes. Visualization: Utilizing visualization tools like Tableau and PowerBI to present findings in a compelling and understandable manner. Cloud-Based Deployment: Deploying models on cloud platforms such as MS Azure, GCP, and AWS, optimizing their functionality and scalability. What we are looking for? Proficiency in Python, SQL, data science modeling, and statistical analysis. Strong grasp of ML algorithms and their implementation in real-world scenarios. Experience in visualization tools like Tableau and PowerBI, along with knowledge of deploying models on cloud platforms (MS Azure, GCP, AWS). Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have e
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Solutions Architects Manager in Pune
95 active opportunities · Updated October 2026
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Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Addepar has just launched an Alternatives Product offering that gives Addepar clients the option to have their Private Funds data extracted, processed, validated, and ingested directly from Private Fund documents for a more automated end-to-end solution for handling Alternatives on the platform. This white-glove solution combines proprietary machine learning technology that automatically extracts data from Private Funds documents and human-in-loop review to validate any documents that fail to pass confidence and data quality checks. As a Senior Lead of the Alternatives Data Operations, you will lead the operations function that is responsible for the human-in-loop review of Private Funds documents, ensuring clients' Alternatives data is processed, validated, and available in Addepar in a timely manner. You will manage a team of Alternatives Data Ops analysts who review Private Fund statements, modify data that has been incorrectly extracted by our machine learning models, and reprocess data within SLAs. In this role, you'll own the operational strategy, team performance, and continuous improvement of the Alternatives Data Ops function—a critical component of Addepar's Alternatives offering success. Your responsibilities will include b
Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Addepar has just launched an Alternatives Product offering that gives Addepar clients the option to have their Private Funds data extracted, processed, validated, and ingested directly from Private Fund documents for a more automated end-to-end solution for handling Alternatives on the platform. This white-glove solution combines proprietary machine learning technology that automatically extracts data from Private Funds documents and human-in-loop review to validate any documents that fail to pass confidence and data quality checks. As part of the broader Addepar Data organization, the Alternatives Data Ops team is responsible for the human-in-loop review of Private Funds documents, ensuring clients' Alternatives data is processed, validated, and available in Addepar in a timely manner. This role will include managing a team and reviewing Private Fund statements, modifying data that has been incorrectly extracted by our machine learning models, and reprocessing the data within SLAs. The Alternatives Data Ops team plays a critical role in the success of Addepar's Alternatives offering and requires daily communications with the Alternatives Product Team, Machine Learning Operations, clients, data providers (GPs and Fund Admins), and add
We are seeking a qualified Senior Software Tools Development Engineer to join our GPU SWQA team. The successful candidate will have strong experience applying AI technologies to automate test cases and a deep understanding of Windows operating systems. Extensive knowledge of GPU, CPU, SoC, x86, and ARM architectures is required, along with expertise in PC I/O architecture and common bus interfaces such as PCIe, USB, and SATA. Familiarity with specifications for general PC architecture components is a plus. What you’ll be doing: Design and implement automated tests incorporating AI technologies for NVIDIA's device driver software and SDKs on windows platforms. Build tools/utility/framework in Python, C# or equivalent which would help automate and optimize the testing workflows in GPU domain. Develop and carry out automated and manual tests, analyze results, identify and report defects. Rigorously drive test automation initiative. Build innovative ways to automate and expand our software testing. Expose defects and constraints; Isolate and debug the issue(s) and find the root cause; Contribute to the solution and drive to closure. Measure code coverage for the software under test, analyze and drive code coverage enhancements. Develop applications and tools that accelerate development and test workflows and write fast, effective, maintainable, reliable and well documented code. Generate and test compatibility across a range of products and interfaces and validate different key software applications across a test matrix designed to test both breadth and depth. Provide peer code reviews including feedback on performance, scalability and correctness. Report test coverage and Go/No-Go status for deliverables, escalate critical issues, and drive them to closure. Participate in root cause analysis and corrective actions to continuo
We are seeking a qualified Software Tools Development Engineer to join our GPU SWQA team. The successful candidate will have strong experience applying AI technologies to automate test cases and a deep understanding of Windows operating systems. Extensive knowledge of GPU, CPU, SoC, x86, and ARM architectures is required, along with expertise in PC I/O architecture and common bus interfaces such as PCIe, USB, and SATA. Familiarity with specifications for general PC architecture components is a plus. What you’ll be doing: Design and implement automated tests incorporating AI technologies for NVIDIA's device driver software and SDKs on windows platforms. Build tools/utility/framework in Python, C# or equivalent which would help automate and optimize the testing workflows in GPU domain. Develop and implement automated and manual tests, analyze results, identify and report defects. Rigorously drive test automation initiative. Build innovative ways to automate and expand our software testing. Expose defects and constraints; Isolate and debug the issue(s) and find the root cause; Contribute to the solution and drive to closure. Measure code coverage for the software under test, analyze and drive code coverage enhancements. Develop applications and tools that accelerate development and test workflows and write fast, effective, maintainable, reliable and well documented code. Generate and test compatibility across a range of products and interfaces and validate different key software applications across a test matrix designed to test both breadth and depth. Provide peer code reviews including feedback on performance, scalability and correctness. Report test coverage and Go/No-Go status for deliverables, escalate critical issues, and drive them to closure. Participate in root cause analysis and corrective actions to continuously im
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