Job Description
Join Nexus Analytics at the forefront of data-driven innovation! We're seeking a visionary Senior Data Scientist to transform complex datasets into actionable business strategies. In this pivotal role, you'll leverage cutting-edge machine learning techniques to solve high-impact challenges across fintech, healthcare, and e-commerce verticals. Collaborate with elite engineers and product leaders to build scalable AI solutions that drive measurable growth and competitive advantage.
Our award-winning culture combines technical rigor with creative freedom. Enjoy competitive benefits including equity, flexible work arrangements, and dedicated R&D time. If you're passionate about turning data into breakthrough innovations, we want to meet you.
Responsibilities
- Design and implement end-to-end machine learning pipelines for predictive modeling and optimization
- Translate complex business problems into data-driven solutions using statistical analysis and ML algorithms
- Collaborate with engineering teams to deploy models at scale using cloud technologies (AWS/GCP)
- Develop compelling data visualizations and executive dashboards using Tableau/Power BI
- Lead A/B testing frameworks to validate model performance and drive product improvements
- Mentor junior data scientists and champion best practices in data governance
- Present findings to C-level stakeholders and influence strategic decision-making
Qualifications
- MSc/PhD in Statistics, Computer Science, or quantitative field with 5+ years industry experience
- Expert proficiency in Python (Scikit-learn, TensorFlow) and SQL with large datasets
- Proven track record of deploying production ML systems with measurable business impact
- Strong statistical foundation: experimental design, hypothesis testing, causal inference
- Experience with cloud data platforms (BigQuery, Redshift, Snowflake)
- Exceptional communication skills translating technical concepts to non-technical audiences
- Portfolio demonstrating complex data science projects with clear ROI documentation