quantitative researcher

VENERABLE

<p></p><div><div><p>Title: Quantitative Researcher/Developers</p><p></p><p>
Employer: VIAC Services Company (Venerable)</p><p></p><p>
Location: West Chester, PA</p><p></p><p>
Job Description:
</p><p>Evaluate the embedded market risks inherent to Variable Annuity products and builds an understanding of how those risks are strategically managed through a hedge program and investment portfolio while attempting to reduce risk to a strategically acceptable level. Assist in the research of theoretical valuation methodologies and models for derivatives and/or financial instruments. Assist in the implementation of practical valuation solutions for the business to utilize. Work toward attaining a high level of knowledge of the derivatives and/or investments contained in the company portfolio. Utilize code libraries for market consistent valuations, statistics, solve optimization problems, analytics and attributions. Enhance tools required to analyze strategic hedging, investment and business decisions and develop a strong knowledge of market parameters and their impact on the value of VA Products and financial/derivative instruments within the company portfolio. Performs research, ad-hoc analysis and report. Assists in the application of scalable technology to support the business and enhance the efficiency of our main profit centers and manage large data sets; consultation on database structures, organize data, and work on database optimization and testing new system components and features.</p><p></p><p>
Minimum Requirements:
</p><p>Master&rsquo;s degree or foreign equivalent in Quantitative Finance, Data Analytics, Computer Science, or closely related field. Must have experience or academic training with the following: Statistics, Modeling, and Regression; performing Quantitative/analytic reasoning, problem-solving abilities, and applying numerical methods to business problems; knowledge of systems design and development principles, database design, optimization and technologies; utilizing reporting tools SQL and PowerBI; performing data analysis utilizing Python and/or R; and designing &amp; developing ETL processes using tools like SSIS or Knime to extract, transform, and load data from multiple sources.</p><p>
#LI-DNI</p></div><p></p><p><b>
Venerable Values:</b></p><p>
Every position at Venerable has responsibility for living out the company's values as described here:</p><p></p><p><b>
We are Courageous - </b>We think critically, ask &quot;why?&quot; and seek out creative solutions.</p><p><b>
We are Curious</b> - We take calculated risks, learn from out failures, and challenge traditional ways of thinking.</p><p><b>
We are Connected</b> - We are connected to each other, our customers and our community.</p><p></p><p><b><i>
Please note:</i></b><i> The use of AI tools (such as ChatGPT or similar platforms) during interviews is not permitted without the prior approval of Venerable, as the use of such tools may interfere with company confidentiality, misrepresent a candidate&rsquo;s skills and experience or otherwise conflict with Venerable&rsquo;s hiring policies. If you are selected for an interview and a reasonable accommodation is needed, please notify the Venerable Human Resources recruiter aligned to the open position in which you are interviewing for.</i></p><p></p><p><i><br>
If Venerable, in its sole discretion, determines that AI is being used during an interview without prior approval, Venerable reserves the right to end the interview early and/or disqualify a candidate.</i></p></div>

Quantitative Researcher/Developers

XTX Markets

<div><p><b>The Firm</b><br>
<br>
XTX Markets is a leading algorithmic trading firm. We build models that forecast prices for more than 53,000 financial instruments across equities, fixed income, currencies, commodities and crypto. Those forecasts are used to trade on exchanges and other venues, and to provide liquidity to clients. The firm trades over $250bn a day across 35 countries, with over 300 people in London, Singapore, New York, Paris, Bristol, Mumbai, Yerevan and Kajaani.</p>
<p>
XTX is a technology business. Trading here is driven by research, large-scale computation and careful engineering. Over the last decade our models have moved from the econometric methods that gave the firm its name, through trees and neural networks, to modern deep learning. We expect that evolution to continue, and we are looking for researchers who can push it.</p>
<p>
The research platform is large by any standard, and particularly unusual in trading: well over 25,000 GPUs and more than 1 exabyte of usable storage, with further compute being built in Finland. The point is simple: good ideas should not be bottlenecked by data, infrastructure or compute.</p><br>
<p><b>
The Team</b><br>
<br>
This role sits in XTX's central Quantitative Research team, the group responsible for the firm's core forecasting research. The team reports directly to XTX's founder and is intentionally flat. There is little ceremony and little hierarchy; researchers are expected to have ideas, test them properly, argue from evidence and get useful work into the system.</p>
<p>
The work is modern ML research, not finance by another name. You do not need to have worked in trading. The best candidates usually have strong research taste, mathematical depth and the ability to make models work in practice. An interest in markets helps, because the domain is full of useful structure, but trading intuition can be built here.</p><br>
<p><b>
The Role</b><br>
<br>
Trading is a hard setting for machine learning in ways that are not always obvious from outside the industry. The data is enormous, messy, non-stationary and produced by other agents. Signals are weak and often short-lived. Evaluation is unforgiving: costs, latency, risk and capacity all matter, and a model that looks good in a backtest may still be useless in the market. The time scales also range from microseconds to weeks, so there is no single right abstraction.</p>
<p>
Your job will be to do original research that improves XTX's forecasting and trading systems. Depending on your background, that may mean:</p>
<ul>
<li>Designing and training deep learning models for large-scale time-series and cross-sectional prediction.</li>
<li>Improving representations, objectives, optimisation, regularisation, uncertainty estimates, evaluation methods or scaling.</li>
<li>Making models more robust under distribution shift and feedback from the market.</li>
<li>Working with engineers and trading technologists to turn research into production systems.</li>
<li>Learning enough market structure to ask better modelling questions.</li>
</ul>
<p>This is not about applying standard methods to tidy datasets. It is a place to do serious ML research on difficult data, with enough compute and infrastructure for ambitious ideas to be tested properly.</p><p><br>
<b>
What We Are Looking For</b></p>
<ul>
<li>Evidence of original technical ability in ML, statistics, mathematics, computer science, physics or another quantitative field. Publications are one route, but not the only one; strong industrial research or major open-source contributions can also be good evidence.</li>
<li>Deep practical understanding of modern deep learning: architectures, objectives, optimisation, scaling, evaluation and failure modes.</li>
<li>Strong mathematical and statistical foundations.</li>
<li>Excellent programming ability and comfort working close to the details of implementation.</li>
<li>Good experimental taste: forming hypotheses, designing clean tests, reading ambiguous results and changing your mind quickly when the evidence changes.</li>
<li>High standards, intellectual honesty and the ability to work in a flat team where ideas are challenged directly.</li>
<li>No finance background is needed; the important thing is being willing to learn the domain.</li></ul><br>
<p><br>
<b>Beneficial Experience</b></p>
<ul>
<li>PhD or equivalent research experience in a relevant technical field.</li>
<li>Experience training large models or building ML systems at meaningful scale.</li>
<li>Work in time-series modelling, online or continual learning, reinforcement learning, causal inference, probabilistic modelling, optimisation, compilers, HPC or low-latency systems.</li>
<li>Experience taking research beyond a prototype.</li><br>
</ul>
<p><b>Benefits</b></p>
<p>
Key benefits include:</p>
<ul>
<li>Onsite gym, sauna and fitness classes.</li>
<li>Extensive medical benefits, including onsite doctor and therapist.</li>
<li>Breakfast and lunch provided daily.</li>
<li>Support for caregivers, including emergency dependent care.</li>
<li>King's Cross office.</li>
<li>25 days paid holiday per year, plus statutory holidays and paid sick days.</li>
<li>Generous pension contributions.</li></ul></div>

Quantitative Researcher - Deep Learning

ENTRIX

<div><h4 class="jobSectionHeader"><b>Short Facts</b></h4><p><b>
Join us on our journey at </b><b>Entrix</b>: We are looking for an experienced Quantitative Researcher to shape how we trade flexibility from our customers' battery assets across European power markets. We operate in markets that run 24/7 (DAA, IDC, aFRR, and others), meaning every model decision we make turns into real positions, real risk, and real revenue. In this role you will guide the next generation of algorithmic trading at Entrix to keep us at the forefront of innovation. Sitting at the intersection of quantitative research and applied data science, you will own the alpha generation pipeline behind our algorithms, from signal research and<br>
backtesting through to live trading and P&amp;L attribution.<br>
<br>
This is a staff-level individual contributor role where you will spend your time on the hardest problems in the team: framing ambiguous trading challenges, designing systems that combine machine learning and optimization to deliver impactful results, and mentoring data scientists to raise the bar across the team. As one of the most senior members of the team, you will own the technical vision for our trading algorithms, help drive the team roadmap, and mentor a strong group of individual contributors working on the hardest problems in the European energy transition.</p><br>
<ul><li>
Location: Munich, Germany</li><li>
Employment Type: Full-Time, indefinite term</li><li>
Salary Range: &euro; 115.000 - 135.000 per year gross depending on the seniority level</li><li>
Office-first work setup</li><li>
Language Requirement: C1 Level English</li></ul><p></p><h4 class="jobSectionHeader"><b><br>
Your Responsibilities</b></h4><p></p><ul><li>
Shape the technical vision and roadmap for our algorithmic trading stack, breaking that vision into work the team can deliver, communicating trade-offs, and driving alignment on methodology, success metrics, and system design.</li><li>
Research, develop, and productize forecasts and strategies that generate alpha by trading flexibility in real-time European energy markets (DAA, IDC, aFRR, etc.), combining ML and optimization techniques to make 24/7 trading decisions.</li><li>
Enhance our the backtesting, simulation, and P&amp;L attribution capabilities that turn research into live strategies, with rigorous overfitting controls, risk-adjusted evaluation, and automated testing.</li><li>
Foster technical excellence across the team by mentoring data scientists through design and code review, and by championing engineering rigor in code quality, observability, and reproducibility.</li><li>
Own the delivery of complex, ambiguous projects from research to production.</li></ul><p></p><h4 class="jobSectionHeader"><b><br>
Your Profile</b></h4><p><b>
Mandatory Requirements</b></p><ul><li>
7+ years industry experience in quantitative research or applied data science, with significant time developing live trading algorithms in energy or financial markets.</li><li>
Proven track record of P&amp;L contribution from strategies you researched, backtested, and shipped to live trading.</li><li>
Deep understanding of trading mechanics: price formation, market microstructure, execution, slippage, risk, and position sizing.</li><li>
Strong fundamentals in time series modelling under non-stationarity and regime shifts, with disciplined backtesting practice (risk-adjusted metrics, overfitting controls, walk-forward validation).</li><li>
Strong expertise in python and software engineering practices: testing, code review, CI/CD, monitoring, modular code design, and taking machine learning and/or optimization models from research into production systems.</li><li>
Track record of mentoring junior team members and raising the technical bar of the team.</li><li>
University degree in Computer Science, Mathematics, Physics, or a related quantitative field.</li>
Excellent English communication and interpersonal skills.<br>
<li>
</li></ul><b>
Skills to Set You Apart</b><ul><li>
Direct experience trading battery storage, flexibility, or other assets in European power markets.</li><li>
Experience combining machine learning (forecasting, signal generation) with mathematical optimization (LP, MILP, stochastic) in a single production-level system.</li><li>
Experience with financial derivatives (especially options), market making, or HFT systems.</li></ul><p></p><h4 class="jobSectionHeader"><b><br>
Your Benefits</b></h4><p></p><ul><li><b>
Competitive Compensation Package</b>: Including salary, benefits, and potential for growth.</li><li><b>
Professional Development</b>: Annual development budget of &euro;3,000 for coaching, training, books, etc.</li><li><b>
Health &amp; Sport Subsidy</b>: Company-subsidized sports facility memberships.</li><li><b>
Public Transportation Subsidy</b>: Monthly subsidy for your public transport ticket.</li><li><b>
Lunch/Dinner Allowance Vouchers</b>: Digital meal vouchers for workdays.</li><li><b>
Work Equipment</b>: Your choice of MacBook or Windows Laptop and ergonomic workplace setup.</li><li><b>
Regular Team Events</b>: Knowledge sessions, afterwork hangouts, sports events, and company offsites.</li></ul><p></p><h4 class="jobSectionHeader"><b>
A Short Note from Your Future Lead</b></h4><p>
I&rsquo;m Austin Todd, Data Science Manager at Entrix. I lead our team of Data Scientists developing innovative algorithms for energy trading and optimization. In my career I&rsquo;ve had many exciting challenges and opportunities, with a consistent focus on developing innovative technical solutions in the energy industry and facilitating a transition to green energy solutions.<br>
<br>
Here&rsquo;s a quick snapshot of my journey so far:</p><ul><li>
Data Science Manager @ sonnen (2021&ndash;2026): Built and scaled cross-functional data science teams, shaping the company vision for data science and AI development.</li><li>
Data Scientist IV @ NREL (2019&ndash;2021): Led research &amp; development efforts for data science applications in wind and solar energy, transportation, and data center operations.</li><li>
Lead Data Scientist @ MeteoGroup (2017&ndash;2018): Drove the development of ML applications to build risk management tools for energy grid transmission operators.</li><li>
Data Scientist @ Telekom Innovation Labs (2015-2017): Supported new client acquisition for Deutsche Telekom through building of innovative data science solutions.</li></ul>
Having spent most of my career building data science applications in the energy industry, I bring both a deep technical knowledge of data science methodology and an understanding of how they can help shape the future of industry like energy. As a manager, I help my teams by fostering innovation and research while driving rapid development that has a meaningful impact. At Entrix, we believe great tech starts with great people. Collaboration, creativity, and an unrelenting focus on delivering results are at the heart of everything we do.<br>
<br>
If you&rsquo;re ready to work with a team that&rsquo;s reshaping industries and tackling some of the toughest challenges, I&rsquo;d love for you to check out our opportunities. Join us, and let&rsquo;s build something extraordinary together.<br>
<br>
Looking forward to seeing what we can create.<p></p><h4 class="jobSectionHeader"><b>
Your Contact in our People Team</b></h4><p>
If you have any questions, feel free to send us an email to talent@entrixenergy.com.<br>
<br>
We are looking forward to receiving your application!</p><h4 class="jobSectionHeader"><b>
&Uuml;ber uns</b></h4><p></p><h4 class="jobSectionHeader"><b>
Wir sind Energieh&auml;ndler und Marktf&uuml;hrer f&uuml;r die Vermarktung von flexiblen Energiesystemen in Europa.</b></h4><br>
Entrix bietet zus&auml;tzlich zu Stromhandel basierend auf k&uuml;nstlicher Intelligenz, innovative Produkte zu langfristiger Umsatzabsicherung und netzdienlichen Steuerung von Batteriespeichern. Mit unserem Rundum-Sorglos-Paket begleiten wir unsere Kunden &uuml;ber alle Projektphasen von der technischen Auslegung und Integration, &uuml;ber die kontinuierliche Optimierung bis zur 24/7 Betreuung im laufenden Betrieb &ndash; inklusive Anpassung an Marktver&auml;nderungen und Erschlie&szlig;ung neuer Erl&ouml;spotenziale.<br>
<br>
Mit &uuml;ber 2,3 GW und 38 Batteriespeichern unter Vertrag ist Entrix in Deutschland, Polen, Italien, Spanien und Portugal aktiv und mit B&uuml;ros in M&uuml;nchen, Warschau, Mailand und Madrid vertreten. Entrix optimiert als Pionier seit 2022 einen der ersten Batteriegro&szlig;speicher in Deutschland und ist heute der bevorzugte Partner f&uuml;hrender Infrastrukturunternehmen wie Encavis, MEAG (Munich Re) sowie eine Vielzahl lokaler Stadtwerke.</div><p></p>

Staff Quantitative Researcher – Energy Trading (f/d/m)

Systematic FX / Futures Sub-Portfolio Manager

Ipsos

<div><p><b>Key Responsibilities
</b></p><ul><li>Support diverse USPA project teams in addressing client research needs via developing efficient and robust study designs, and executing comprehensive, advanced inferential and predictive analyses.
</li><li>Assist senior researchers in generating complex weighting adjustments using machine learning as well as classical statistical procedures, implementing variance adjustments for survey inferences, blending samples, and monitoring data quality.
</li><li>Prepare internal and external data for analysis, and review data as they come in from the field.
</li><li>Serve as supporting author on client technical deliverables, as well as narrative proposals.
</li><li>Actively contribute to technical literature reviews and solutioning sessions in the domains of statistics, data science, causal inference, synthetic data, and data integration.
</li><li>Work as part of interdisciplinary project teams to interpret and cross-validate study findings, develop visualizations and insights, and communicate results to clients and stakeholders.
</li>Interface with other technical teams across Ipsos to facilitate effective deployment of high performance computing resources.<br>
<li>
</li></ul><p></p><p><b>The Ideal Candidate has the following Skills, Experience, and Attributes
</b></p><ul><li>Masters or PhD in statistics, biostatistics, data science, computer science, or a relevant highly-quantitative social or behavioral science field.
</li><li>Between 3-6 years of experience (depending on credential) in an applied research settings, preferably serving Federal or state statistical or policy agencies in the domains of population and / or behavioral research.
</li><li>Experience with Bayesian modeling and / or supporting the design and implementation of complex sampling and weighting plans a plus.
</li><li>Formal training in one or more forms of longitudinal data analysis and their application to social and behavioral research (i.e., growth curve modeling, mixed effects models, panel methods, failure time / event history analysis, time series, etc.).
</li><li>Experience with Census, health, public opinion, and demographic data.
</li><li>Advanced skills in R and Python (must have experience using PyTorch); skill in SAS preferred.
</li><li>Ability to convey complex technical topics to non-technical audiences, both verbally and in written form.
</li><li>Proactive, and comfortable working within tight and shifting timelines. Ability to support multiple projects simultaneously, while maintaining a strong client service orientation.
</li><li>Unflagging attention to detail and commitment to the accuracy and completeness of information, quality of results, and robustness of findings.
</li><li>Team player with strong interpersonal skills, and the potential to grow as a multidisciplinary quantitative researcher in a dynamic and entrepreneurial organization.
</li>Flexible and comprehensive thinker with enthusiasm for learning and population research; solid foundation in the theoretical and practical aspects of applying statistics as well as data science tools and principles to custom, hypothesis-driven social and behavioral research.<br>
<li>
</li></ul><p></p><div><div><i>If you don&rsquo;t meet 100% of the requirements, we encourage all who feel they might be a fit for the opportunity to apply. We may consider a variety of backgrounds for a particular role and are also committed to considering candidates for available positions throughout our organization, not just the one you&rsquo;re applying to!<br>
</i></div></div><div></div><div><div><i>In accordance with NY/CO/CA/WA law, the estimated base salary range for this role is $110,000 to $120,000. Your final base salary will be determined based on several non-discriminatory factors which may include but are not limited to location, work experience, skills, knowledge, education and/or certifications.<br>
</i></div></div><div></div><div><div><b>What&rsquo;s in it for you:
</b></div></div><div><div><i>At Ipsos you&rsquo;ll experience opportunities for Career Development, an exceptional benefits package (including generous PTO, healthcare plans, wellness benefits), a flexible workplace policy, and a strong collaborative culture.<br>
</i></div></div><div></div><div><div><i>To find out more about all the great reasons to work at Ipsos, how we&rsquo;re making an impact around the world, and more about our benefits and employee programs, please visit:</i><i><br>
</i>
<br>
Why Work at Ipsos | US
</div></div><div><div>Why Work at Ipsos | CA<br>
</div></div><div></div><div><div><b>Commitment to Diversity
</b></div></div><div><div>Ipsos recognizes the necessity of building an inclusive culture that values each employee&rsquo;s individuality and diverse perspectives. For more than 40 years, our mission has been to generate and analyze data about society, markets, brands, and behaviors to provide our clients with the insights that elevate their understanding of the world. This could not be fulfilled without Ipsos&rsquo; diverse employees who compile and analyze this data&mdash;they are the essence of who we are and what we do.<br>
</div></div><div></div><div><div>We are committed to providing equal opportunity to all employees, creating an environment that promotes inclusion, and enabling employees from all walks of life to flourish. Ipsos encourages our employees to act in a respectful and responsible manner, in line with code of best practices concerning diversity and inclusion, human rights, equality, and civility for every individual.<br>
</div></div><div></div><div><div>Ipsos is An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or any other protected class and will not be discriminated against on the basis of disability.<br>
</div><div></div><div>#LI-TL1 #LI-Hybrid</div></div></div><p></p>

Statistician

DataAnnotation

<div>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 We are looking for existing quantitative professionals to help train AI models. In this role, you will work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analyses, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here. Some team members fit this work alongside a full-time role, while others treat it as their primary focus.
 <br/>
 <br/>
 To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.
 <br/>
 <br/>
 <strong>
  Advantages Of Contracting With Us
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You'll be able to choose which projects you want to work on and when
  </li>
  <li>
   You work on your own schedule, on your own computer, from the comfort of your own home
  </li>
  <li>
   Projects are paid hourly starting at $50-$100+ USD per hour, with bonus rates available on some projects
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity.
  </li>
  <li>
   Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.
  </li>
  <li>
   Write clear technical explanations and well-documented analytical code.
  </li>
  <li>
   Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   2+ years of hands-on experience in a quantitative role or research environment &mdash; such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.
  </li>
  <li>
   Some coding experience required, with comfort writing and reviewing analytical code end-to-end.
  </li>
  <li>
   Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting).
  </li>
  <li>
   Fluency in English (native or bilingual level) with strong writing skills.
  </li>
  <li>
   A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus.
  </li>
  <li>
   Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise).
   <br/>
   <br/>
  </li>
 </ul>
 Note: Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. Only applicants in the United States, Canada, United Kingdom, Ireland, Australia, and New Zealand will be considered for this role. This is an independent contractor position.
 <br/>
 <br/>
 #datascience
</div>


Experimentation Analyst - AI Trainer

Forecasting Analyst - AI Trainer

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