quantitative engineer

Meril

<div>
 <p>
  As a
  <strong>
   Quantitative Machine Learning Engineer
  </strong>
  at
  <strong>
   Merli
  </strong>
  , you will help shape the next generation of
  <strong>
   AI-driven trading infrastructure
  </strong>
  . This role sits at the intersection of
  <strong>
   quantitative research, applied ML, and agentic system design
  </strong>
  , with the goal of optimizing high-frequency (HFT), medium-frequency (MFT), and wholesale trading strategies.
 </p>
 <p>
  You&rsquo;ll architect
  <strong>
   adaptive, agent-based ML systems
  </strong>
  that learn from evolving market microstructures, build robust forecasting and optimization models, and work with trading and infrastructure teams to deploy these solutions in
  <strong>
   real-world, low-latency environments
  </strong>
  .
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Design &amp; Build Agentic ML Systems:
   </strong>
   Develop autonomous and semi-autonomous agents that perform data acquisition, alpha discovery, backtesting, and execution optimization.
  </li>
  <li>
   <strong>
    End-to-End ML Engineering:
   </strong>
   Architect, train, and deploy ML pipelines for HFT/MFT and wholesale trading, from signal generation to execution integration.
  </li>
  <li>
   <strong>
    Quantitative Research Integration:
   </strong>
   Collaborate with quant researchers to translate theoretical models into production-ready predictive and optimization systems.
  </li>
  <li>
   <strong>
    Market Forecasting:
   </strong>
   Develop deep learning, time series, and reinforcement learning models for price movement prediction and regime detection.
  </li>
  <li>
   <strong>
    Trading Optimization:
   </strong>
   Build reinforcement and meta-learning frameworks that adaptively tune strategy parameters in live environments.
  </li>
  <li>
   <strong>
    Scalable ML Infrastructure:
   </strong>
   Implement real-time inference, model versioning, and continuous learning pipelines for production systems.
  </li>
  <li>
   <strong>
    Performance Evaluation:
   </strong>
   Rigorously validate models with historical and synthetic simulations, ensuring robustness, latency, and financial soundness.
  </li>
  <li>
   <strong>
    Documentation &amp; Collaboration:
   </strong>
   Maintain high standards of reproducibility, version control, and code documentation across research and deployment layers.
  </li>
 </ul>
 <p>
  <strong>
   What You&rsquo;ll Gain
  </strong>
 </p>
 <ul>
  <li>
   Work at the frontier of
   <strong>
    AI, quantitative finance, and agentic automation
   </strong>
   .
  </li>
  <li>
   Collaborate with
   <strong>
    quant researchers, data engineers, and trading teams
   </strong>
   shaping next-gen trading systems.
  </li>
  <li>
   Exposure to
   <strong>
    meta-optimization frameworks
   </strong>
   ,
   <strong>
    reinforcement learning
   </strong>
   , and
   <strong>
    multi-agent orchestration
   </strong>
   .
  </li>
  <li>
   Hands-on experience with
   <strong>
    low-latency ML deployment
   </strong>
   , GPU acceleration, and distributed training in real trading environments.
  </li>
  <li>
   Ownership of models that directly influence
   <strong>
    market-making, forecasting, and strategy execution
   </strong>
   .
  </li>
  <li>
   Continuous learning and experimentation in a
   <strong>
    research-first, innovation-driven
   </strong>
   environment.
  </li>
 </ul>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s, Master&rsquo;s, or Ph.D. in Computer Science, Applied Mathematics, Financial Engineering, or a related quantitative field.
  </li>
  <li>
   <strong>
    3+ years
   </strong>
   of experience developing and deploying ML models in production (preferably in finance, trading, or large-scale decision systems).
  </li>
  <li>
   Strong proficiency in
   <strong>
    Python
   </strong>
   and ML frameworks:
   <em>
    PyTorch, TensorFlow, scikit-learn, NumPy, Pandas
   </em>
   .
  </li>
  <li>
   Deep understanding of
   <strong>
    supervised, unsupervised, and reinforcement learning
   </strong>
   ,
   <strong>
    time-series modeling
   </strong>
   , and
   <strong>
    probabilistic forecasting
   </strong>
   .
  </li>
  <li>
   Experience building
   <strong>
    scalable data pipelines
   </strong>
   with
   <em>
    Kafka, Flink, or Ray
   </em>
   and deploying models in
   <em>
    Docker/Kubernetes
   </em>
   environments.
  </li>
  <li>
   Knowledge of
   <strong>
    market microstructure
   </strong>
   ,
   <strong>
    portfolio optimization
   </strong>
   , or
   <strong>
    signal-based trading systems
   </strong>
   is highly desirable.
  </li>
  <li>
   Familiarity with
   <strong>
    meta-learning
   </strong>
   ,
   <strong>
    agent-based system design
   </strong>
   , or
   <strong>
    multi-agent coordination
   </strong>
   is a strong plus.
  </li>
  <li>
   Solid analytical, programming, and debugging skills with an emphasis on
   <strong>
    system reliability and latency optimization
   </strong>
   .
  </li>
 </ul>
 <p>
  <strong>
   Preferred Technical Stack
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Languages:
   </strong>
   Python, C++, Rust
  </li>
  <li>
   <strong>
    ML Infrastructure:
   </strong>
   Ray, MLflow, Airflow, Weights &amp; Biases
  </li>
  <li>
   <strong>
    Data Systems:
   </strong>
   Kafka, Redpanda, Redis, QuestDB
  </li>
  <li>
   <strong>
    Model Deployment:
   </strong>
   Triton Inference Server, TorchServe, or custom GPU inference
  </li>
  <li>
   <strong>
    Cloud/Hybrid Setup:
   </strong>
   Kubernetes, ArgoCD, Helm
  </li>
 </ul>
 <p>
 </p>
</div>


Quantitative ML Engineer

Goldman Sachs

<div><div><div><div><div><div><div>Division Summary
<p>
Goldman Sachs&rsquo; Strats business unit is a world leader in developing quantitative models and technologies to solve complex business problems. Working within the firm&rsquo;s trading, sales, banking, and asset management divisions, strats use their mathematical and scientific training to create financial products, advise clients on transactions, measure risk, and identify market opportunities. Investment Banking Strats are involved in marketing, structuring, pricing, and executing transactions for large corporations and institutions in the capital markets and M&amp;A. We develop state-of-the-art quantitative and analytical methods for advising clients and build financing and risk-management solutions across products and industries.<br>
<br>
Investment Banking Strats are both investment bankers and innovators who create analytics and scalable technology platforms that will shape the future of investment banking and how we connect with clients. Direct participation in client interactions, deal executions, and other core commercial activities allows us to be in the optimal position to develop technical innovations that create economic leverage and differentiate the firm. We ensure maximum technical efficacy by encouraging fluency in the latest quantitative models, data science, data engineering, and software platforms through peer learning, MOOC-like curated learning, and online training resources.<br>
</p><p>Our team members are quantitative engineers, financial engineers, and data scientists who share a passion for investment banking and the financial markets.<br>
<br>
<b>Job Summary &amp; Responsibilities</b></p><br>
<p></p>
<p>
We are looking for an Associate / Analyst to join the Investment Banking M&amp;A Quant Advisory team in Bengaluru. This is a desk strat role. The position involves solving business problems using large and complex financial datasets and working in tandem with Investment Bankers across different industry and regions. We produce differentiated client analytics, which are utilized in M&amp;A deals and adding further data-driven content in coverage teams&rsquo; interaction with clients. We utilize machine learning and big data analysis tools to create proprietary targeting solutions.</p><br>
<p></p>
<p>
A successful candidate must act as a local liaison with our global team, and interact with Classic Banking, the Financing Group, Global Markets, and other Investment Banking Engineering teams. We expect them to be self-led, entrepreneurial, and capable of managing the delivery and adoption of key products.</p><br>
<p></p>
Responsibilities<br>
<p></p>
<ul><li>Develop state-of-the-art quantitative and analytical methods for targeting new transaction opportunities.</li></ul>
<ul><li>Develop supportive ideas and solutions to solve questions from both internal and external clients, which can cover deal performance analysis, competitor analysis, and deal execution strategy.</li></ul>
<ul><li>Develop new tools to make data and analytics accessible to a broad range of internal users.</li></ul>
<ul><li>Program in Python or other languages utilizing machine learning and statistical methods.</li></ul>
<ul><li>Create and maintain curated datasets based on raw data sources from multiple vendors that best serve our analytics and different business purposes.</li></ul>
<ul><li>Build reports, analyses, and alerts to efficiently generate materials and data visualization for internal management, business monitoring, risk management, and opportunity targeting.</li></ul><br>
<p></p>
Basic Qualifications, Skills &amp; Experience<br>
<p></p>
<ul><li>Bachelor&rsquo;s or advanced degree in a quantitative/ STEM discipline (e.g., Mathematics, Computer Science, Engineering, Statistics etc.)</li></ul>
<ul><li>2+ years of quantitative modeling and development experience</li><li>Strong quantitative / analytic reasoning and problem-solving abilities</li><li>Strong technical and computer programming skills in an Object-oriented programming language such as Python</li></ul>
<ul><li>Strong data management skills in data querying languages including SQL and MongoDB</li><li>Strong oral and written communication skills</li><li>Strong interpersonal skills; desire and ability to play on a team</li><li>Strong interest in finance, investment banking, and the capital markets</li><li>Results-oriented work ethic based upon responsibility, enthusiasm, and pride in work</li></ul>
 Preferred Qualifications<br>
<p></p>
<ul><li>Experience in M&amp;A and / or Capital Markets</li></ul><br>
<p></p>
<p><b>
About Goldman Sachs, EEO Statement</b></p><br>
<p></p>
<p><i>
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.</i></p>
<p><i>
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. about our culture, benefits, and people at GS.com/careers.</i></p>
<p><i>
We&rsquo;re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. : https://www.goldmansachs.com/careers/footer/disability-statement.html</i></p>
<p><i>
&copy; The Goldman Sachs Group, Inc., 2020. All rights reserved.</i></p>
<p><i>
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity</i></p></div></div></div></div></div></div><div><div><div><div><div><b>
We Offer Best-In-Class Benefits</b></div></div></div><p></p><div><div><div><div><div><div><div>
Healthcare &amp; Medical Insurance</div></div><p>
We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Holiday &amp; Vacation Policies</div></div><p>
We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Financial Wellness &amp; Retirement</div></div><p>
We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees&rsquo; priorities.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Health Services</div></div><p>
We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Fitness</div></div><p>
To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount).</p></div></div></div></div><p></p><div><div><div><div><div><div>
Child Care &amp; Family Care</div></div><p>
We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Benefits at Goldman Sachs</div></div><p>
Read more about the full suite of class-leading benefits our firm has to offer.</p></div></div></div></div></div></div></div></div><div></div>
<br><p>Opportunity Overview
CORPORATE TITLE
Associate
OFFICE LOCATION(S)
Bengaluru
JOB FUNCTION
Banking Analysis
DIVISION
Global Banking &amp; Markets</p>

GBM - Private - M&A Quant Advisory -Associate-Bengaluru

Qube Research & Technologies

<p><br></p>
<p> <strong>Your future role within QRT:</strong> </p>
<p>As a Quantitative Developer, you'll work in a close-knit global team of Multi-Asset Quant Developers and Researchers. Working directly with Researchers and Portfolio Managers, you'll enhance our research platform to meet the needs of a constantly evolving environment. You will have a large impact on the success of the team by recommending innovative software solutions - solving problems by building new tools and systems.</p>
<p> <strong>Responsibilities</strong> </p>
<ul>
<li>Automate and streamline data preparation and cleaning</li>
<li>Build and support new quantitative trading framework</li>
<li>Industrialize trading strategies developed by quant researchers</li>
<li>Drive "best practice" amongst the researchers and portfolio managers</li>
<li>Continually expand and upgrade the team s software platform to accommodate the changing business needs</li>
</ul>
<p> <strong>Your present skillset:</strong> </p>
<ul>
<li>3-8 years of experience as a software engineer</li>
<li>Python language experience is a must</li>
<li>Ability to multitask, set project priorities and work in a team</li>
<li>Strong communication skills is a must</li>
<li>Ability to work in a fast-paced environment</li>
<li>Very high standards in code quality and good development practices</li>
<li>Experience in finance and/or machine learning would be beneficial</li>
</ul>
<p><br></p>

Quantitative Developer - Python

HE Holding LLC

<p>Job Description:</p><ul><li>Obtaining quotations and preparation of price comparison report to get the best.</li><li>Prepare and issue POs to vendors with all necessary approvals.</li><li>Follow up with vendors and ensure timely delivery of items ordered.</li><li>Investigate qualitative and quantitative discrepancies between goods ordered and goods received.</li><li>Responsible for the accurate processing of materials receipts.</li><li>Generate monthly procurement reports, identity, and investigate unusual items and report accordingly.</li><li>Arrange good quality materials from suppliers at the right time and reasonable price</li></ul><p><b>Qualifications</b></p><ul><li>Bachelor&rsquo;s degree in civil engineering or mechanical engineering with minimum 4 years of working experience as a procurement engineer in contracting company</li></ul><p>Note:- Visit visa holders or urgently available candidates will be preferred</p><p>Job Types: Full-time, Permanent</p><p>Pay: AED3,500.00 - AED5,000.00 per month</p>

Procurement Engineer

<div>
 <p>
  <strong>
   About the Role
  </strong>
 </p>
 <p>
  As a
  <strong>
   Quantitative Data Engineer
  </strong>
  , you will be the backbone of the data ecosystem powering our
  <strong>
   quantitative research, trading, and AI-driven strategies
  </strong>
  . You will design, build, and maintain the
  <strong>
   high-performance data infrastructure
  </strong>
  that enables low-latency, high-fidelity access to market, fundamental, and alternative data across multiple asset classes.
 </p>
 <p>
  This role bridges
  <strong>
   quant engineering, data systems, and research enablement
  </strong>
  , ensuring that our researchers and traders have fast, reliable, and well-documented datasets for analysis and live trading. You&rsquo;ll be part of a cross-functional team working at the intersection of
  <strong>
   finance, machine learning, and distributed systems
  </strong>
  .
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Architect and maintain scalable ETL pipelines
   </strong>
   for ingesting and transforming terabytes of structured, semi-structured, and unstructured market and alternative data.
  </li>
  <li>
   <strong>
    Design time-series optimized data stores
   </strong>
   and
   <strong>
    streaming frameworks
   </strong>
   to support low-latency data access for both backtesting and live trading.
  </li>
  <li>
   <strong>
    Develop ingestion frameworks
   </strong>
   integrating vendor feeds (Bloomberg, Refinitiv, Polygon, Quandl, etc.), exchange data, and internal execution systems.
  </li>
  <li>
   <strong>
    Collaborate with quantitative researchers and ML teams
   </strong>
   to ensure data accuracy, feature availability, and schema evolution aligned with modeling needs.
  </li>
  <li>
   <strong>
    Implement data quality checks, validation pipelines, and version control mechanisms
   </strong>
   for all datasets.
  </li>
  <li>
   <strong>
    Monitor and optimize distributed compute environments
   </strong>
   (Spark, Flink, Ray, or Dask) for performance and cost efficiency.
  </li>
  <li>
   <strong>
    Automate workflows
   </strong>
   using orchestration tools (Airflow, Prefect, Dagster) for reliability and reproducibility.
  </li>
  <li>
   <strong>
    Establish best practices
   </strong>
   for metadata management, lineage tracking, and documentation.
  </li>
  <li>
   <strong>
    Contribute to internal libraries and SDKs
   </strong>
   for seamless data access by trading and research applications.
  </li>
 </ul>
 <p>
  <strong>
   In Trading Firms, Data Engineers Typically:
  </strong>
 </p>
 <ul>
  <li>
   Build
   <strong>
    real-time data streaming systems
   </strong>
   to capture market ticks, order books, and execution signals.
  </li>
  <li>
   Manage
   <strong>
    versioned historical data lakes
   </strong>
   for backtesting and model training.
  </li>
  <li>
   Handle
   <strong>
    multi-venue data normalization
   </strong>
   (different exchanges and instruments).
  </li>
  <li>
   Integrate
   <strong>
    alternative datasets
   </strong>
   (satellite imagery, news sentiment, ESG, supply-chain data).
  </li>
  <li>
   Work closely with
   <strong>
    quant researchers
   </strong>
   to convert raw data into
   <strong>
    research-ready features
   </strong>
   .
  </li>
  <li>
   Optimize pipelines for
   <strong>
    ultra-low latency
   </strong>
   where milliseconds can impact P&amp;L.
  </li>
  <li>
   Implement
   <strong>
    data observability frameworks
   </strong>
   to ensure uptime and quality.
  </li>
  <li>
   Collaborate with
   <strong>
    DevOps and infra engineers
   </strong>
   to scale storage, caching, and compute.
  </li>
 </ul>
 <p>
  <strong>
   Tech Stack
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Languages:
   </strong>
   Python, SQL, Scala, Go, Rust (optional for HFT pipelines)
  </li>
  <li>
   <strong>
    Data Processing:
   </strong>
   Apache Spark, Flink, Ray, Dask, Pandas, Polars
  </li>
  <li>
   <strong>
    Workflow Orchestration:
   </strong>
   Apache Airflow, Prefect, Dagster
  </li>
  <li>
   <strong>
    Databases &amp; Storage:
   </strong>
   PostgreSQL, ClickHouse, DuckDB, ElasticSearch, Redis
  </li>
  <li>
   <strong>
    Data Lakes:
   </strong>
   Delta Lake, Iceberg, Hudi, Parquet
  </li>
  <li>
   <strong>
    Streaming:
   </strong>
   Kafka, Redpanda, Pulsar
  </li>
  <li>
   <strong>
    Cloud &amp; Infra:
   </strong>
   AWS (S3, EMR, Lambda), GCP, Azure, Kubernetes
  </li>
  <li>
   <strong>
    Version Control &amp; Lineage:
   </strong>
   DVC, MLflow, Feast, Great Expectations
  </li>
  <li>
   <strong>
    Visualization / Monitoring:
   </strong>
   Grafana, Prometheus, Superset, DataDog
  </li>
  <li>
   <strong>
    Tools for Finance:
   </strong>
   kdb+/q (for tick data), InfluxDB, QuestDB
  </li>
 </ul>
 <p>
  <strong>
   What You Will Gain
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    End-to-end ownership
   </strong>
   of core data infrastructure in a high-impact, mission-critical domain.
  </li>
  <li>
   Deep exposure to
   <strong>
    quantitative research workflows
   </strong>
   ,
   <strong>
    market microstructure
   </strong>
   , and
   <strong>
    real-time trading systems
   </strong>
   .
  </li>
  <li>
   <strong>
    Collaboration with elite quantitative researchers, traders, and ML scientists.
   </strong>
  </li>
  <li>
   Hands-on experience with
   <strong>
    cutting-edge distributed systems
   </strong>
   and
   <strong>
    time-series data technologies
   </strong>
   .
  </li>
  <li>
   A culture that emphasizes
   <strong>
    technical excellence, autonomy, and experimentation.
   </strong>
  </li>
 </ul>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s in
   <strong>
    Computer Science, Data Engineering, or related field.
   </strong>
  </li>
  <li>
   <strong>
    2+ years
   </strong>
   of experience building and maintaining
   <strong>
    production-grade data pipelines
   </strong>
   .
  </li>
  <li>
   Proficiency in
   <strong>
    Python
   </strong>
   ,
   <strong>
    SQL
   </strong>
   , and frameworks like
   <strong>
    Airflow
   </strong>
   ,
   <strong>
    Spark
   </strong>
   , or
   <strong>
    Flink
   </strong>
   .
  </li>
  <li>
   Familiarity with
   <strong>
    cloud storage and compute (S3, GCS, EMR, Dataproc)
   </strong>
   and
   <strong>
    versioned data lakes (Delta, Iceberg)
   </strong>
   .
  </li>
  <li>
   Experience with
   <strong>
    financial datasets
   </strong>
   ,
   <strong>
    tick-level data
   </strong>
   , or
   <strong>
    high-frequency time series
   </strong>
   is a strong plus.
  </li>
  <li>
   Strong understanding of
   <strong>
    data modeling, schema design, and performance optimization
   </strong>
   .
  </li>
  <li>
   Excellent communication skills with an ability to support
   <strong>
    multidisciplinary teams
   </strong>
   .
  </li>
 </ul>
 <p>
 </p>
</div>


Data Engineer – Financial Infrastructure & Analytics

CELESTAL

<div>
 <p>
  <strong>
   Risk Analysis Engineer
  </strong>
 </p>
 <p>
  We are seeking a skilled
  <strong>
   Risk Analysis Engineer
  </strong>
  to support the identification, assessment, and mitigation of risks across
  <strong>
   offshore and onshore oil &amp; gas projects
  </strong>
  . This role is crucial in ensuring project safety, reliability, and performance through proactive and systematic risk management.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities:
  </strong>
 </p>
 <ul>
  <li>
   Perform
   <strong>
    qualitative and quantitative risk assessments
   </strong>
   , including
   <strong>
    HAZID, HAZOP, LOPA, and QRA
   </strong>
   studies.
  </li>
  <li>
   Collaborate with multidisciplinary teams to identify
   <strong>
    technical, operational, and financial risks
   </strong>
   .
  </li>
  <li>
   Develop and implement
   <strong>
    risk management strategies
   </strong>
   and
   <strong>
    mitigation plans
   </strong>
   to minimize exposure.
  </li>
  <li>
   Maintain and update
   <strong>
    risk registers
   </strong>
   , ensuring timely reporting to management and project stakeholders.
  </li>
  <li>
   Provide
   <strong>
    technical support and guidance
   </strong>
   on risk-related issues to engineering and project management teams.
  </li>
  <li>
   Prepare and present
   <strong>
    risk analysis reports
   </strong>
   to internal and external stakeholders.
  </li>
  <li>
   Support compliance with
   <strong>
    safety, environmental, and quality standards
   </strong>
   through proactive risk management.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications and Experience:
  </strong>
 </p>
 <p>
  🎓
  <strong>
   Education:
  </strong>
  Bachelor&rsquo;s degree in
  <strong>
   Mechanical, Electrical, Chemical, or related Engineering field
  </strong>
  .
 </p>
 <p>
  🌍
  <strong>
   Experience:
  </strong>
  Minimum
  <strong>
   5 years of experience
  </strong>
  in
  <strong>
   risk analysis
  </strong>
  within the
  <strong>
   oil &amp; gas industry
  </strong>
  , preferably with
  <strong>
   offshore project exposure
  </strong>
  .
 </p>
 <p>
  💼
  <strong>
   Technical Skills:
  </strong>
  Strong understanding of
  <strong>
   risk management methodologies
  </strong>
  (HAZID, HAZOP, FMEA, QRA) and familiarity with industry standards such as
  <strong>
   API, ISO, IEC
  </strong>
  . Excellent analytical, problem-solving, and communication skills.
 </p>
 <p>
  <br/>
 </p>
 <p>
  If you are ready to apply your expertise to complex offshore and onshore projects while driving
  <strong>
   safe and efficient project outcomes
  </strong>
  , we&rsquo;d love to hear from you!
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Come and join us on our Life page!
  </strong>
  ➡️
  <u>
   Celestal-Life
  </u>
 </p>
 <p>
  🌍
  <strong>
   Become a Celes&rsquo;Talent &mdash; ready to shape the future with us?
  </strong>
 </p>
</div>


Risk Analysis Engineer

Luxoft

<div><div><h5 class="jobSectionHeader"><b>Project description
</b></h5><p>We're seeking a Senior Software Engineer to design and build robust, scalable systems that support portfolio and risk analytics, order and trade lifecycle processing, and investment strategies. You will work closely with portfolio managers, quantitative analysts, and product teams to develop technology solutions that create tangible business value in the capital markets space.
</p></div><div><h5 class="jobSectionHeader"><b>Responsibilities</b></h5>
<div><div><p>Key Responsibilities (%70 Backend/30% Frontend)
</p></div><div><p>Design and implement end-to-end technology solutions in an Agile environment, collaborating with business and technical partners.
</p></div><div><p>Leverage AWS cloud services to build scalable, cloud-native applications aligned with long-term architecture goals.
</p></div><div><p>Build and maintain CI/CD pipelines, automated tests, and infrastructure-as-code for efficient deployment.
</p></div><div><p>Ensure system performance, reliability, and scalability across mission-critical applications.
</p></div><div><p>Drive engineering excellence through coding best practices, technical mentorship, and peer collaboration.
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Skills</b></h5>
<p>Must have
</p><div><div><p>10+ years of experience with Java in enterprise systems
</p></div><div><p>5+ years of Spring Boot
</p></div><div><p>3+ years of React
</p></div><div><p>5+ years working with relational databases (e.g., PostgreSQL, MySQL)
</p></div><div><p>5+ years developing and deploying systems on AWS
</p></div><div><p>Demonstrated experience in Capital Markets, Portfolio Management, or Risk Analytics
</p></div><div><p>Strong analytical and problem-solving skills
</p></div><div><p>Excellent verbal and written communication skills
</p></div></div><p>Nice to have
</p><div><div><p>Preferred Skills
</p></div><div><p>Familiarity with AWS
</p></div><div><p>Experience with containerization (e.g., Docker, Kubernetes)
</p></div><div><p>Working knowledge of DevOps practices and tools such as Terraform, GitHub Actions, or Jenkins
</p></div><div><p>Exposure to quantitative models, financial data, or multi-asset strategies
</p></div><div><p>Comfortable working in fast-paced, regulated environments with high-performance expectations
</p></div><div><p>What We're Looking For
</p></div><div><p>Independent self-starter who thrives in an entrepreneurial environment
</p></div><div><p>Strong interpersonal skills and ability to communicate with diverse stakeholders, including front-office professionals, PMs, and quants
</p></div><div><p>Highly organized with exceptional attention to detail and the ability to manage multiple priorities
</p></div><div><p>Professional, adaptable, and collaborative team player
</p></div><div><p>Results-oriented mindset with the ability to deliver under tight deadlines
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Other</b></h5>
<div><div><div><p>Languages</p>
<p>English: C2 Proficient
</p></div></div><div><div><p>Seniority</p>
<p>Senior</p></div></div></div></div></div>
<br><div><div><div><p>Mumbai, India
</p></div><p>Req. VR-118730
</p></div><div></div><div><div><p>Java Full Stack
</p></div><div><p>BCM Industry</p>
</div><div><p>30/10/2025
</p></div><div><p>Req. VR-118730</p></div></div></div><p></p>

Full Stack Developer

Search 8811+ Quantitative engineer jobs near you this October. New roles added regularly across leading industries. Apply today.