Data Scientist

Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now!  

Tickmill is looking to hire a Data Scientist to join our rapidly expanding team.   

The successful candidate will drive customer-centric machine learning initiatives that directly impact our bottom line, owning the complete ML lifecycle from problem definition to low-latency production deployment on our Azure Databricks stack.

This hands-on role significantly influences customer personalization, marketing ROI, fraud prevention, and client lifetime value in our fast-paced trading environment.

Join a high-caliber team and contribute to its success with your passion, hard work and positive attitude.

About Tickmill.   

Tickmill is an award-winning, multi-regulated broker offering a wide range of asset classes including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies and bonds, as well as Exchange Traded Derivatives (Futures & Options).

The Tickmill Group was established in 2014 and employs over 290 individuals through its offices in London, Cyprus, Estonia and several other regional offices globally.

Our philosophy is based on trust, transparency, and diversity, reflected in both our workplace culture and outstanding customer support. Our employees, a multilingual team of highly skilled professionals from every continent, are the backbone of the company. Their hard work and dedication are what makes it possible to rank among the best in the industry. Tickmill offers a comprehensive benefits package like anniversary bonuses, birthday half-day off, well-being schemes, team-building events, and opportunities for professional growth.

What the job looks like?

The Data Scientist will have the opportunity to:

• Develop sophisticated behavioral, transactional, and demographic models for personalized product offerings and targeted campaigns.
• Build and refine predictive LTV models to optimize acquisition costs and guide resource allocation.
• Create advanced churn prediction models, collaborating with product/marketing teams to design and test retention interventions.
• Develop lead scoring and conversion propensity models to maximize marketing ROI on high-potential prospects plus design uplift models and A/B/n testing frameworks to optimize promotional strategies and incentive programs.

• Build low-latency, real-time fraud and bonus abuse prevention models using behavioral analytics and advanced classification techniques to minimize financial exposure.
• Partner with compliance and trading operations to identify suspicious patterns, reduce platform abuse, and protect business integrity.

• Ensure model outputs align with financial regulations (e.g., MiFID II, GDPR) and maintain comprehensive audit trails. Clearly present model insights, assumptions, and actionable recommendations to senior leadership and non-technical stakeholders.

• Manage the full ML lifecycle: feature engineering, model training, validation, low-latency deployment, monitoring, and automated retraining in production.
• Build and maintain robust, production-ready data pipelines and ML workflows using Azure Databricks, Delta Lake, MLflow, and Apache Spark for both batch and real-time processing and inference.
• Champion MLOps best practices including model monitoring, drift detection, A/B testing frameworks, version control, CI/CD, and automated alerting.

• Translate complex business requirements from product, marketing, risk, trading, and finance teams into scalable data science solutions.
• Help shape the organization's data governance, experimentation culture, and overall data & analytics strategy.

What will you need to be able to do the job?

• Minimum 3 years of hands-on data science experience with a proven track record of building and deploying ML models in production environments with measurable business impact.
• Prior experience in financial services, trading platforms, fintech, or high-volume B2C environments is highly preferred.
• Deep understanding and practical experience with customer analytics use cases (segmentation, churn prediction, LTV modeling, fraud detection, experimentation design).
• Hands-on experience with Supervised & Unsupervised learning methods, Deep Learning, Time Series analysis, NLP, and LLMs.
• Strong Python (pandas, scikit-learn, XGBoost, LightGBM, PySpark) and SQL proficiency.
• Hands-on expertise with the Azure Databricks ecosystem (Delta Lake, MLflow, Apache Spark, Notebooks).
• Experience with low-latency model deployment (REST APIs, containerization), streaming data processing, version control (Github), and production monitoring.
• Strong foundation in statistical modeling, hypothesis testing, causal inference, and experimental design.
• Excellent knowledge of the English Language both written and oral.
• Collaborative mindset with proven cross-functional team experience, curiosity, self-motivation, passion for continuous learning and staying abreast of the latest ML advancements.
• Bachelor’s or Master’s Degree in Data Science, Statistics, Computer Science, Mathematics, Econometrics, Physics, or a related quantitative field.

Will be a plus if you have:

• Experience with advanced techniques like uplift modeling, multi-armed bandits, or time series forecasting in financial contexts.
• Understanding of financial markets, trading behavior, and regulatory requirements specific to CFD/forex environments.
• Interest in mentoring junior team members and contributing to data science best practices and ability to influence business strategy discussions through data-driven insights.

By joining us, you can expect:

• A Unique Opportunity for a career in a global, fast-growing company.
• Attractive remuneration package based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance).
• Opportunities to learn and grow through our “Employee Training & Development program”.
• Medical Insurance Cover, which includes Outpatient, Inpatient, and Dental Care.
• Multiple events to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company.
• Participation in our welfare investment and savings plan through our Provident Fund Scheme.
• Birthday half day off.
• Loyalty benefits.
• Collaboration with SportBenefit.

What to expect from our recruitment process:

• Interview with HR
• Interview with hiring managers
• Psychometric test
• Final interview with top management
  

Make your next Career step and apply NOW!

*Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.