Jobs at Newbridge

Our client is a global institutional investor managing capital at scale across public and private markets. The mandate for this team is simple: turn data into edge, and edge into decisions.These are not back-office support roles. You will sit inside the investment and research workflow. Your code, models, and pipelines will touch live capital allocation, risk, and alpha generation. The bar is high because the data is proprietary and the users are portfolio managers, not analysts.We are hiring across three tracks. You can apply to one or multiple if your profile spans them.Note: All roles are Individual Contributor positions. Our client is hiring across multiple levels — from strong mid-level to Principal/Staff1. Data Scientist – Investment ResearchMissionBuild and deploy models that extract signal from structured and unstructured data to inform discretionary and systematic investment decisions.ScopePartner directly with sector PMs and researchers to frame ambiguous problems as testable hypothesesDevelop ML/NLP/time-series models on alternative data, market data, and fundamental datasetsProductionize research: your notebook isn’t the deliverable — the monitored, versioned model isExplain trade-offs to non-technical stakeholders. “The AUC is 0.82” is not an answer.Profile We’re Calibrating ForExperience quant research, data science, or ML engineering with direct exposure to financial marketsStrong Python + SQL. Experience with scientific stack: pandas, scikit-learn, PyTorch/TensorFlow, statsmodelsComfort with messy, real-world data. You’ve joined 12 tables to build one feature and lived to tell about itMSc/PhD in STEM, Stats, CS, Financial Engineering preferred, but we’ll take a killer GitHub over a logoYou think in base rates and Bayesian updates, not just in accuracy scores2. Data Engineer – Investment PlatformMissionDesign and run the data backbone that feeds research, backtesting, and production trading. Latency, lineage, and correctness are your P&L.ScopeBuild and maintain high-throughput pipelines for market, reference, alternative, and fundamental dataArchitect storage + compute: think petabyte-scale, cloud-native, but cost-awareImplement data quality, observability, and entitlement frameworks. Bad data here loses real moneyEnable quants and DS to self-serve without creating a ticket or waiting 3 daysProfile We’re Calibrating For4-10 years building production data systems, ideally in finance, trading, or high-stakes analyticsPython/Scala/Java + SQL. Spark, Airflow, Kafka, dbt, Snowflake/BigQuery/DatabricksDeep understanding of partitioning, versioning, and replay. “It works on my laptop” is a fireable offenseYou design for failure. Your pipelines have DLQs, retries, and alerts that actually wake someone upBonus: experience with market data, tick data, point-in-time correctness, corporate actions3. Quantitative Developer – Systematic StrategiesMissionSit between research and production. Take prototype strategies and make them run fast, clean, and safely with real capital.ScopeTranslate researcher code into low-latency, testable, production-grade systems — C++/Python/RustBuild sim/backtest frameworks that match production behavior. No “research vs prod” driftOwn tooling for signal generation, portfolio construction, risk checks, and execution hooksProfile, optimize, and harden. When the market opens, your code doesn’t get a second chanceProfile We’re Calibrating For3-10 years as a quant dev, low-latency dev, or SWE in trading/systematic fundsStrong C++ or Python with performance intuition. You know why virtual functions hurt and when to use them anywayLinux, git, CI/CD, numerical computing. You’ve debugged a race condition at 2am before a US openUndergrad/MS in CS, Math, Physics, Engineering. Competitive programming/ICPC background is a plusYou respect researchers but you don’t ship their for-loops to prodShared DNA Across All Three RolesOur client hires for three traits regardless of track:Ownership – You ship, you support, you fix. No “not my system” here.Rigor – Financial data has no undo button. Test it, document it, prove it.Low ego, high output – The PM is your customer. Your job is to make them better, not to publish papers.Hiring ProcessTypically 3 rounds: Technical deep-dive → System/research design → CIO/Head of Platform.We move in days, not months. Take-home tests are rare; live problem solving is common. Show more Show less