A Senior Data Scientist role at IBM CIC involves leading AI solutions with a keen focus on foundation and large language models, offering the unique differentiator of embedded mentorship and...
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A Senior Data Scientist role at IBM CIC involves leading AI solutions with a keen focus on foundation and large language models, offering the unique differentiator of embedded mentorship and client relationships. The main risk is the need to keep up with rapidly evolving AI technologies, which could make current expertise quickly obsolete. Salary details are not provided; tools include Python, TensorFlow, PyTorch, cloud platforms like AWS, Azure, GCP, and AI frameworks. The role is categorized as data_scientist, and the position is not intermediated.
Kantar Media's Data Engineer role in London leans more toward service QA and data inputs validation than pure pipeline building. The long title sits atop a job that asks you to audit data...
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Kantar Media's Data Engineer role in London leans more toward service QA and data inputs validation than pure pipeline building. The long title sits atop a job that asks you to audit data processing, understand architecture, and shore up ‘service correctness’ across multi-country first-party data and panel inputs. It promises exposure to Azure cloud, Linux, shell scripting, Python, and SQL, but the bulk of work reads like quality assurance within a measurement stack rather than crafting scalable data platforms. That may suit veterans who enjoy debugging reproducibility and data lineages; less so if you’re chasing hands-on ETL, streaming, or modern orchestration tooling. The company’s pedigree and global footprint are real positives, but you’ll contend with corporate processes, compliance and a hybrid-work policy that still nudges you into the office at Grays Inn Road. Overall, solid steadiness, caution on growth.
The BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of...
PIMCO's London front-office quant blends academic rigor with trading desk pragmatism: initial value assessments, novel pricing of bespoke features, and post-trade surveillance across ABF, loans,...
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PIMCO's London front-office quant blends academic rigor with trading desk pragmatism: initial value assessments, novel pricing of bespoke features, and post-trade surveillance across ABF, loans, SRTs, unsecured lending and consumer credit. The candidate must be highly technical, versed in asset pricing theory and probability, with a front-office background, and able to turn models into Python code inside a substantial codebase. Intex and SPV mechanics are a plus; Linux/Unix and SQL are expected. It stands out for tying model development directly to PM collaboration and risk-adjusted return signals at a global scale, not just academic exercises. The catch is its narrow domain and steep prerequisites, which limit supply and make the role sensitive to market and regulatory shifts; salary details are absent, as is any explicit career progression path.
The role at DRW is a high-impact, fast-paced data analyst position requiring expertise in financial data processing, cloud workflows, and data quality engineering. The job emphasizes hands-on data...
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The role at DRW is a high-impact, fast-paced data analyst position requiring expertise in financial data processing, cloud workflows, and data quality engineering. The job emphasizes hands-on data validation, process optimization, and cross-team collaboration, with a focus on real-world problem-solving and technical precision. While the role offers opportunities to work with cutting-edge tools like PySpark and Airflow, it also demands rigorous attention to detail and the ability to navigate complex data pipelines. The company values innovation and autonomy, aligning with a culture that rewards creativity and technical depth. The role is not an intermediary position, and the salary range is not explicitly provided.
Six-month full-time Technical Support Intern at SAS's CareerStart program in the UK, London or Marlow, hybrid with three on-site days and two remote. It’s pitched as real work for interns,...
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Six-month full-time Technical Support Intern at SAS's CareerStart program in the UK, London or Marlow, hybrid with three on-site days and two remote. It’s pitched as real work for interns, tackling customer-reported problems, escalations, and cross-border collaboration with a global team, plus hands-on internal projects that touch the tech stack but likely stop short of building data pipelines. Requires STEM or engineering/CS background; comfortable with Windows, Unix, and Linux; basic Python, R, SQL; SAS programming is a bonus and cloud/data analytics familiarity helps. The lure is genuine exposure - executive time, training, and a SAS certification - but the downside is the internship label in a vendor-dominated space with unclear compensation and limited infrastructure work. For data professionals, useful if you want enterprise software experience and SAS pedigree; risky if you seek hands-on engineering scale and modern cloud pipelines.
Quantitative Developer - AI Implementation
@ worldquant
GB | 2025-12-23
WorldQuant is hiring a Full-Time Software Engineer to harden an AI-driven platform that links proprietary strategy tooling with Large Language Models. The role centers on designing, deploying, and...
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Quantitative Developer - AI Implementation
worldquant
(GB) CONTRACT | JOB LISTED
WorldQuant is hiring a Full-Time Software Engineer to harden an AI-driven platform that links proprietary strategy tooling with Large Language Models. The role centers on designing, deploying, and maintaining Model Context Protocol (MCP) servers in Python, building new MCPs for data integration, analytics, and performance reporting, and stitching together secure prompt engineering to keep intellectual property intact while enabling natural-language interactions for portfolio managers. Expect work on APIs, data parsing (JSON/CSV), Pandas, data pipelines, and data security in a Linux/Git environment. Familiarity with financial data and quantitative trading systems is a bonus. The position trades off buzzword compliance for real impact in data access patterns and reliability; it’s niche, technically demanding, and offers a chance to shape internal data platforms, not just ride AI hype.
A Senior Data Scientist role at IBM CIC involves leading AI solutions with a keen focus on foundation and large language models, offering the unique differentiator of embedded mentorship and client relationships. The main risk is the need to keep up with rapidly evolving AI technologies, which could make current expertise quickly obsolete. Salary details are not provided; tools include Python, TensorFlow, PyTorch, cloud platforms like AWS, Azure, GCP, and AI frameworks. The role is categorized as data_scientist, and the position is not intermediated.
Kantar Media's Data Engineer role in London leans more toward service QA and data inputs validation than pure pipeline building. The long title sits atop a job that asks you to audit data processing, understand architecture, and shore up ‘service correctness’ across multi-country first-party data and panel inputs. It promises exposure to Azure cloud, Linux, shell scripting, Python, and SQL, but the bulk of work reads like quality assurance within a measurement stack rather than crafting scalable data platforms. That may suit veterans who enjoy debugging reproducibility and data lineages; less so if you’re chasing hands-on ETL, streaming, or modern orchestration tooling. The company’s pedigree and global footprint are real positives, but you’ll contend with corporate processes, compliance and a hybrid-work policy that still nudges you into the office at Grays Inn Road. Overall, solid steadiness, caution on growth.
PIMCO's London front-office quant blends academic rigor with trading desk pragmatism: initial value assessments, novel pricing of bespoke features, and post-trade surveillance across ABF, loans, SRTs, unsecured lending and consumer credit. The candidate must be highly technical, versed in asset pricing theory and probability, with a front-office background, and able to turn models into Python code inside a substantial codebase. Intex and SPV mechanics are a plus; Linux/Unix and SQL are expected. It stands out for tying model development directly to PM collaboration and risk-adjusted return signals at a global scale, not just academic exercises. The catch is its narrow domain and steep prerequisites, which limit supply and make the role sensitive to market and regulatory shifts; salary details are absent, as is any explicit career progression path.
The role at DRW is a high-impact, fast-paced data analyst position requiring expertise in financial data processing, cloud workflows, and data quality engineering. The job emphasizes hands-on data validation, process optimization, and cross-team collaboration, with a focus on real-world problem-solving and technical precision. While the role offers opportunities to work with cutting-edge tools like PySpark and Airflow, it also demands rigorous attention to detail and the ability to navigate complex data pipelines. The company values innovation and autonomy, aligning with a culture that rewards creativity and technical depth. The role is not an intermediary position, and the salary range is not explicitly provided.
Six-month full-time Technical Support Intern at SAS's CareerStart program in the UK, London or Marlow, hybrid with three on-site days and two remote. It’s pitched as real work for interns, tackling customer-reported problems, escalations, and cross-border collaboration with a global team, plus hands-on internal projects that touch the tech stack but likely stop short of building data pipelines. Requires STEM or engineering/CS background; comfortable with Windows, Unix, and Linux; basic Python, R, SQL; SAS programming is a bonus and cloud/data analytics familiarity helps. The lure is genuine exposure - executive time, training, and a SAS certification - but the downside is the internship label in a vendor-dominated space with unclear compensation and limited infrastructure work. For data professionals, useful if you want enterprise software experience and SAS pedigree; risky if you seek hands-on engineering scale and modern cloud pipelines.
Quantitative Developer - AI Implementation
worldquant
(GB) CONTRACT | JOB LISTED
WorldQuant is hiring a Full-Time Software Engineer to harden an AI-driven platform that links proprietary strategy tooling with Large Language Models. The role centers on designing, deploying, and maintaining Model Context Protocol (MCP) servers in Python, building new MCPs for data integration, analytics, and performance reporting, and stitching together secure prompt engineering to keep intellectual property intact while enabling natural-language interactions for portfolio managers. Expect work on APIs, data parsing (JSON/CSV), Pandas, data pipelines, and data security in a Linux/Git environment. Familiarity with financial data and quantitative trading systems is a bonus. The position trades off buzzword compliance for real impact in data access patterns and reliability; it’s niche, technically demanding, and offers a chance to shape internal data platforms, not just ride AI hype.
