Job Category: Remote
Job Type: Full Time
Skills: A/B Testing AI Governance Amazon SageMaker Behavioral Analytics Cloud Computing (AWS/GCP) Data Architecture Data Science Generative AI Kubernetes Machine Learning PostgreSQL Product Strategy Python R Snowflake SQL Statistics Vertex AI
Qualifications
Bachelor’s degree in Computer Science, Data Science, Statistics, or a related quantitative field (Master’s preferred); 0-2 years of hands-on experience in data science, product-oriented model development, and deployment.
Job Details
Responsibilities
Product-Oriented Data Science
- Design and deploy scalable statistical models and machine learning solutions for intelligent products and customer-facing experiences
- Apply ML and Generative AI to drive innovation in areas like personalization, recommendation engines, and automation
Data Architecture and Engineering Collaboration
- Partner with Data Engineering to define robust data architecture
- Build scalable data pipelines supporting real-time analytics, experimentation, and training
Advanced Analytics & Business Strategy Alignment
- Translate complex business problems into actionable insights
- Guide product development and marketing strategy through behavioral analytics, customer segmentation, and cohort analysis
AI Governance and Responsible Innovation
- Advocate for responsible AI practices including fairness, transparency, and model accountability
- Ensure compliance in handling financial and personal data
Cross-Functional Collaboration
- Work with product managers, designers, engineers, and external partners to embed data science into every step of the product lifecycle
- Influence strategic decision-making through data-driven storytelling and presentations
Model Optimization & Experimentation
- Leverage A/B and multivariate testing to optimize product performance
- Iterate models based on feedback and experimentation outcomes
Innovation & Industry Awareness
- Stay updated with the latest in AI/ML, especially LLMs and generative models
- Bring emerging frameworks and tools into the development lifecycle
Skills and Qualifications
- Technical Proficiency: Expert in Python or R, SQL, and experience with cloud-based databases (Snowflake, PostgreSQL, MySQL)
- Machine Learning Expertise: Proven experience with model building, generative AI, LLMs, and open-source toolkits
- Cloud & Orchestration: Familiarity with AWS/GCP, and orchestration tools like SageMaker, Vertex AI, Step Functions
- Analytics Strength: Strong command over statistical modeling, causal inference, uplift/attribution modeling
- Communication & Leadership: Ability to explain complex models to non-technical stakeholders and influence product roadmaps
- Domain Experience (Preferred): Prior work in regulated domains (FinTech, Healthcare, Insurance), with an understanding of data privacy and compliance
Certifications (Preferred)
- TensorFlow Developer Certification
- AWS Certified Machine Learning – Specialty
- Google Cloud Professional Data Engineer
- Responsible AI certifications (e.g., from Microsoft or IBM)
