Job Description

Company Description

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.

By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.

From prototype to real-world impact - be part of a global shift by doing work that matters.

Job Description

We are seeking a Data Scientist to design, build and validate the machine learning models behind personalization features in our new mobile trading app, working within guardrails set by our Compliance team.

What they will do

• Build similar-symbol models (clustering / co-occurrence) on aggregate trading data, including minimum-activity thresholds
• Develop propensity models that score customers’ likelihood to adopt new products, from day one of the customer lifecycle
• Explore models linking significant price moves to news events
• Define features, training data and evaluation metrics; validate models and set score thresholds
• Analyze content and in-app engagement data to identify drop-off and high-performing content
• Hand off production-ready models to ML Engineers and document methodology and assumptions

Qualifications

Must have

• 4+ years in applied data science, with models deployed to production
• Strong Python and SQL; scikit-learn, XGBoost/LightGBM or similar
• Recommendation systems, clustering and propensity / classification modeling
• Experimental design and model evaluation (A/B testing, calibration, drift)
• Ability to explain modeling choices clearly to product and compliance stakeholders

Nice to have

• Brokerage, trading or other financial services experience
• Knowledge of options and equities markets
• Product analytics data (e.g. Amplitude)

Additional Information

Discover some of the global benefits that empower our people to become the best version of themselves:

• Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus;
• Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
• Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
• Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
• Health: Global internal wellbeing programme, access to wellbeing apps;
• Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.

At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.