Lead Business Data Scientist at Exness jobs for internal candidates

✨ The Stack take on this Exness jobs for internal candidates job

• 🏢 Exness jobs for internal candidates has 13 jobs here, 13 with visa sponsorship see all
• 🛂 Visa: Foreign Interest Company work permit. Minimum salary: €2,500 a month guide
• 💡 No salary shown. Ask Exness jobs for internal candidates if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Partner with product, business and engineering stakeholders to identify high-impact problems and define success criteria.
- Translate ambiguous business questions into well-posed statistical or ML problems and deliver MVPs quickly.
- Own end-to-end lifecycle: data discovery, modeling, validation, deployment, monitoring and impact measurement.
- Design and analyze A/B tests and apply causal-inference approaches when randomization isn’t possible.
- Build forecasts, segmentations, attribution and uplift models when justified; prefer simplest effective solution.
- Productionize robust, reproducible ML pipelines (clean Python, tests, scheduling, version control, CI/CD).
- Communicate probabilistic insights and trade-offs to non-technical audiences and drive recommendations to impact.
- Mentor peers, run code reviews and contribute to team knowledge-sharing and standards.

Requirements:
- Degree in a quantitative field (Math, CS, Engineering) and 5+ years in Data Science/Product Analytics.
- Strong fundamentals in probability and statistics and practical applied ML experience (including LLM integrations).
- Engineering discipline: clean Python, automated tests, advanced SQL (window functions, performance), CI/CD and MLOps experience.
- Proven autonomy, stakeholder management, strong communication and ability to prioritize business impact over complexity.

Responsibilities

Partner with business stakeholders to translate ambiguous problems into data and ML solutions across Trading, Partnerships, Payments, and Client Relationships. Own the full lifecycle from data discovery and MVP development to deployment, monitoring, and driving actual business change.

Requirements

Requires a quantitative degree and 5+ years of experience in Data Science or Product Analysis with strong fundamentals in probability and statistics. Must possess strong engineering skills in Python and SQL, experience with LLMs, and the ability to manage stakeholders effectively.

Key skills

• Machine Learning — in 291 other listings on The Stack
• Python — in 1200 other listings on The Stack
• SQL — in 545 other listings on The Stack
• Probability — in 11 other listings on The Stack
• Statistics — in 53 other listings on The Stack
• Causal Inference — in 18 other listings on The Stack
• A/B Testing — in 124 other listings on The Stack
• LLMs — in 80 other listings on The Stack
• CI/CD
• Stakeholder Management
• Data Analysis
• Forecasting
• Segmentation
• Attribution Modeling
• Uplift Modeling
• ML Pipelines

On The Stack (as of 2026-11-05)

• Exness jobs for internal candidates has 12 other listings on The Stack, 12 of them marked as offering visa sponsorship.
• 34 visa-sponsored jobs in Cyprus on The Stack, posted in the last 60 days.
• 68 visa-sponsored data scientist jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about Exness jobs for internal candidates

Is this Lead Business Data Scientist role still open?

It was posted on 2026-06-22. Listings more than 30 days old may no longer be active, so check Exness jobs for internal candidates's site before applying.

Does Exness jobs for internal candidates offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Exness jobs for internal candidates's site.

Where is this role located?

The listing gives the location as Cyprus. It is marked on-site.

What skills does this role ask for?

The listing names: Machine Learning, Python, SQL, Probability, Statistics, Causal Inference, A/B Testing, LLMs, CI/CD, Stakeholder Management, Data Analysis, Forecasting, Segmentation, Attribution Modeling, Uplift Modeling, ML Pipelines.