Overview
We are looking for a Senior Data Scientist to drive end-to-end data science and machine learning initiatives that enhance business decision-making and operational efficiency. This role requires a blend of technical expertise, strategic thinking, and business acumen to solve complex problems, optimize processes, and build a data-driven culture.
Key Responsibilities
- Apply data science and machine learning techniques to develop and deploy data-driven insights.
- Build and optimize segmentation models, recommendation systems, forecasting solutions, churn prediction models, and product analytics frameworks.
- Design and develop predictive and prescriptive analytics models to support strategic decision-making.
Cross-Functional Collaboration & Business Insights
- Partner with Product, Sales, Engineering, Marketing, and Finance to define data-driven strategies.
- Work with Engineering, Product Management, and Customer Success to analyze product usage trends and develop actionable insights.
- Lead discussions with stakeholders to gather evolving business requirements, define project OKRs and milestones, and communicate progress effectively to non-technical audiences.
Data-Driven Culture & Stakeholder Management
- Advocate for data-driven decision-making across the organization.
- Develop self-service internal data products to empower teams with easy access to relevant insights.
- Represent the data science discipline within the company, ensuring best practices are followed.
Mentorship & Technical Leadership
- Mentor and guide junior data scientists, providing support in project planning, technical decision-making, and code/documentation review.
- Drive continuous improvement in data science methodologies, tools, and processes.
Requirements
- 5+ years of experience in data science and machine learning.
- Strong expertise in Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with Databricks, Spark, or other big data platforms.
- Hands-on experience with recommendation systems, forecasting models, segmentation, and product analytics.
- Strong understanding of A/B testing, statistical analysis, and feature engineering.
- Ability to translate business challenges into data-driven solutions.
- Excellent stakeholder management, communication, and storytelling skills.
Preferred Skills
- Experience in MLOps, model deployment, and cloud platforms (AWS, GCP, Azure).
- Knowledge of deep learning, NLP, and time-series forecasting.
- Prior experience in a high-growth tech environment or SaaS company.