Data Scientist

The Mission: Turning Complex Data into Strategic Gold

Join an elite, top-tier partner in the Financial Services and Technology space. X-Team is seeking a Senior Data Scientist who excels beyond building models in isolation. You will serve as the crucial link between raw data and actionable business strategy, collaborating closely with Product and Engineering teams to deliver analytical solutions that inform high-level decision-making.

The Role: Lead, Architect, and Deploy

This is an end-to-end mission where you will own the entire Data Story for X-Team's clients.

• Predictive Power: Design, develop, and deploy sophisticated statistical and Machine Learning (ML) models to tackle complex business challenges.
• Production-Ready: Move beyond theoretical notebooks to build and maintain robust data pipelines and MLOps monitoring processes, ensuring solution reliability and performance.
• Experimental Design: Spearhead A/B testing, causal inference studies, and forecasting initiatives to quantitatively measure product success and impact.
• Strategic Voice: Effectively communicate complex findings to C-Suite stakeholders, translating intricate mathematical concepts into clear, tangible business growth opportunities.

Must-Haves

• Experience: 5+ years of experience in Data Science, underpinned by a strong theoretical and practical foundation in Statistics, Probability, and Experimental Design.
• The Stack: Demonstrated mastery of Python (including libraries like pandas, NumPy, scikit-learn) and advanced SQL for data manipulation and analysis.
• Cloud & Viz: Hands-on familiarity with major cloud platforms (AWS, GCP, or Azure) and proficiency in data visualization tools such as Tableau or Power BI.
• Production Track Record: Proven experience successfully deploying data science models into live, production environments.

Bonus Skills

• Direct experience within Financial Services or other highly regulated industries.
• Background in MLOps workflows and familiarity with Big Data technologies (e.g., Spark, Hadoop).
• Master’s or PhD in a quantitative field (e.g., Statistics, Computer Science, Mathematics).

Personal Traits

• Analytical Thinking: Possess an eagle eye for detail, with a knack for identifying subtle or hidden patterns within complex datasets.
• Stakeholder Mastery: Exhibit the ability to deftly balance deep technical discussions with clear, concise, and business-focused communication tailored for various audiences.
• Curious & Continuous: Demonstrate a passion for lifelong learning, constantly exploring new frameworks, methodologies, and architectural patterns in the data science landscape.

Key skills/competency

• Data Science
• Machine Learning
• Statistical Modeling
• Python
• SQL
• A/B Testing
• MLOps
• Cloud Platforms (AWS/GCP/Azure)
• Data Visualization
• Causal Inference