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Data Scientist at Trivelta
Monterrey MXFull-timeEngineeringPosted 27 days ago
Apply with PipelineAbout the Role
<div><strong>About the Role</strong></div>
<div> </div>
<div>On Trivelta, we build the technology that powers modern, social-first gaming experiences. Through our proprietary sportsbook and casino engine, we enable partners to launch fully branded, legally compliant gaming products combining real social interactions, predictive gameplay, and casino entertainment in one unified experience.<br>Headquartered in Boston with operations in Monterrey, Barcelona, and Atlanta, we’re scaling rapidly and building a global team passionate about redefining how people play, socialize, and connect.</div>
<div><br>We’re seeking a highly autonomous and full-stack <strong>Data Scientist</strong> to join our team in Monterrey, MX. In this role, you will own the entire data lifecycle—from wrangling raw, untouched datasets to deploying live predictive models. You will be instrumental in taking unexplored areas of our business (such as bonus and promotional data), establishing the reporting baseline, conducting deep exploratory analytics, and ultimately building the live models that drive our operational efficiency and product success.</div>
<div><br><strong>What You’ll Do</strong></div>
<ul>
<li><strong>Own End-to-End Data Projects:</strong> Lead complex initiatives starting from raw, unmeasured data sources (e.g., bonus systems). Write robust, efficient SQL to extract, clean, and structure this data for advanced analysis.</li>
<li><strong>Establish Baseline Metrics:</strong> Design and deploy interactive dashboards using modern BI tools to visualize newly onboarded data, tracking key performance indicators and sharing insights with stakeholders.</li>
<li><strong>Deep Data Analytics:</strong> Conduct rigorous exploratory data analysis (EDA) using tools like Jupyter Notebooks and Python to uncover hidden patterns, user behaviors, and actionable insights from our datasets.</li>
<li><strong>Build and Deploy Live Models:</strong> Translate analytical insights into actionable machine learning solutions. Develop, train, and deploy predictive models to production (live models) to directly increase business efficiency and optimize our gaming experience.</li>
<li><strong>Monitor and Iterate:</strong> Oversee the performance of live models in production, ensuring their accuracy, reliability, and continuous improvement over time.</li>
<li><strong>Cross-Functional Collaboration:</strong> Partner closely with data analysts, engineers, and business leaders to align modeling objectives with overarching company goals.</li>
</ul>
<div><strong>What You Bring</strong></div>
<div> </div>
<div><strong>Must-have</strong></div>
<ul>
<li>Bachelor’s or Master’s degree in a highly quantitative field (Computer Science, Statistics, Mathematics, Data Science, etc.).</li>
<li>3–5+ years of experience in a Data Scientist role with a proven track record of owning projects from data extraction to model deployment.</li>
<li>Strong programming skills in <strong>Python</strong> and extensive experience conducting analysis within <strong>Jupyter Notebooks</strong> (using libraries like pandas, NumPy, scikit-learn).</li>
<li>Advanced, hands-on <strong>SQL</strong> skills for complex data cleaning, transformation, and extraction.</li>
<li>Proven experience developing and maintaining <strong>live models</strong> in a production environment.</li>
<li>Experience building functional reports and dashboards in BI tools (Power BI, Tableau, Looker, etc.) to communicate findings.</li>
<li>Advanced English and strong communication skills, with the ability to explain complex data science concepts to non-technical stakeholders.</li>
</ul>
<div><strong>Nice-to-have</strong></div>
<ul>
<li>Experience working within cloud-based infrastructure, preferably AWS (SageMaker, S3, Redshift, Athena).</li>
<li>Familiarity with data engineering concepts or building basic ETL pipelines.</li>
<li>Prior experience in the gaming, sports betting, or casino industry.</li>
<li>Experience applying advanced ML techniques (e.g., deep learning, reinforcement learning) or graph/network analysis.</li>
</ul>
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