Implementation Engineer

The Opportunity Join Enigma's Growth & KYB Team at a pivotal moment as we continue to create sales and marketing solutions for small businesses. We're seeking an experienced Senior Software Engineer to develop and build innovative data products and systems that directly impact our customers and accelerate our growth. Your work will influence decisions for companies that employ half the U.S. workforce, creating tremendous value for our clients. The Role As a member of the Growth & KYB Team, you will: Design, develop and deliver data products that solve critical customer pain points and build scalable, high-quality systems that deliver rich interactions with our data. Engage with software engineers, data scientists, and product managers to create experiences that move a customer from discovery to evaluation to purchase. Analyze and extract value from data at scale, building efficient, maintainable production-grade data solutions. Create scalable and highly maintainable systems deployed in cloud environments. Own architecture and design decisions as well as hands-on implementation, ensuring that customer experiences are compelling and have low costs of ownership. What You’ll Do Operates with a bias for action and knows how to deliver value in the short, medium, and long term. Loves interacting with product teams and works hard to solve customer problems in a repeatable way. Adopts a principled, metrics-driven approach to difficult data problems and demonstrates excellence in their analytics and engineering craft. Operates transparently, collaboratively, and with low ego—loves learning from others and having their ideas questioned and challenged. Has a “can-do” attitude and thrives on a highly collaborative, cross-functional team that plays a critical role in the company’s success. Is eager to own architecture and design decisions as well as hands-on implementation. What Makes This Role Exciting? Impact : Develop products that take an innovative data-first appro

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! As a Senior Solutions Engineer, you are a commercially minded technical specialist working as a strategic co-pilot alongside New Business Account Executives and Account Managers .Your primary mission is to drive revenue growth, accelerate deal velocity, and ensure technical win rates across active sales opportunities. You bridge the gap between complex technical capabilities and strategic business outcomes, translating Trustpilot's value proposition into compelling commercial solutions for upper mid-market and enterprise companies that instill technical confidence and convert prospects into long-term customers. You partner closely with sales teams during technical discovery to uncover high-value business challenges, map customer requirements to clear commercial outcomes, and drive Annual Contract Value (ACV) growth. This is a high-impact, customer-facing role that combines technical expertise with commercial influence. Success is measured by deal conversion rates, technical win rates, and the quality of handover to implementation. What you’ll be doing: Commercial Discovery & Strategy: Partner closely with Account Executives to uncover high-value business challenges, identify key technical decision-makers, and map customer requirements to clear commercial outcomes. Value-Driven Demonstrations: Deliver tailored, highly engaging product demonstrations that highlight ROI, competitive differentiation, and business impact to align with client commercial goals. Solution Architecture & Revenue Generation: Design and present scalable solution architectures that solve key business pain points, drive expansion, and maxi

ROLE/RESPONSIBILITES Perform rigorous and innovative research to discover systematic anomalies in equity market End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization and production implementation Identify and evaluate new datasets for stock return predictions Maintain and improve the portfolio trading in production environment REQUIREMENTS MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics 1+ years of work experience in systematic alpha research in equities Experience developing short term alpha signals (intraday or a few days) is a plus Demonstrated proficiency in R or Python Strong command of foundations of applied statistics, linear algebra, and time series models Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources Strong knowledge of financial markets Highly motivated, willing to take ownership of his/her work Collaborative mindset with strong independent research ability

About the Team: A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional to develop and trade systematic macro strategies, with a focus on market microstructure. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business. Role/Responsibilities: Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals Perform feature engineering with order book tick data at intraday to daily horizons Perform feature combination using various modeling techniques ranging from linear to machine learning models Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation Help drive the growth of the investment process and research capabilities of the team Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets Assist in building, maintenance, and continual improvement of production and trading environments Requirements: MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics 4+ years of experience in quantitative research, building statistical models for intraday to daily trading, as part of a successful proprietary trading team with a track record Knowledge of market microstructure for futures and/or FX Prior experience with tick data based feature generation, modelling, and monetization Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies. Job Description Develop systematic trading models across FX, commodities, fixed income, and equity markets Alpha idea generation, backtesting, and implementation Assist in building, maintenance, and continual improvement of production and trading environments Evaluate new datasets for alpha potential Improve existing strategies and portfolio optimization Execution monitoring Be a core contributor to growing the investment process and research infrastructure of the team Desirable Candidates Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus Experience in quantitative trading, ideally in FX or futures Experience with alpha research, portfolio construction and optimization Experience building statistical/technical, fundamental, and data driven signals Experience synthesizing predictive signals for both cross-sectional and time-series models Strong experience with data exploration, dimension reduction, and feature engineering Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity Experience managing and running risk is a strong plus Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Creative mindset Strong time management abi

JOB DESCRIPTION Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field. Superb analytical and quantitative skills, along with a healthy streak of creativity. Demonstrated ability to conduct independent research utilizing large data sets. Passion for seeing research through from initial conception to eventual application. Curiosity about financial markets Strong scientific programming in Python, R or Matlab. Empirical, detail-oriented mindset. Sense of ownership of his/her work, working well both independently and within a small collaborative team. We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear abou