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About the Role
Develop models and analysis for AI-powered products, proving their impact with customers. This role involves understanding business problems, exploring data, developing and validating models, and collaborating with engineers for production deployment. It's ideal for someone early in their career seeking ownership and mentorship.
Responsibilities
- Develop, validate, and iterate on models for forecasting, optimization, anomaly detection, and measurement.
- Perform exploratory analysis on complex customer datasets to identify actionable patterns.
- Design and analyze experiments, and build measurement approaches to quantify business impact.
- Establish rigorous validation practices, including backtesting, holdouts, and error analysis.
- Partner with ML and data engineers to move models from notebook to production.
- Contribute to feature engineering, evaluation pipelines, and model monitoring.
- Write clean, reproducible Python code for collaboration and extension.
- Translate business questions into analytical problems and analytical results into recommendations.
- Communicate findings clearly to internal teams and customers, including non-technical audiences.
- Monitor deployed models and ensure they deliver promised results.
Requirements
- Experience developing and validating models on real-world data through internships, prior roles, or substantive project work.
- Solid foundation in statistics and machine learning, including regression, time series, tree-based methods, and experimental design.
- Strong Python skills (pandas, scikit-learn, and ecosystem) and strong SQL.
- Curiosity about the business problem behind the data.
- Clear communication skills to explain technical work to non-technical audiences.
- Strong problem-solving skills, adaptability, and a "hacker" mentality.
- Eagerness to learn quickly in a startup environment.
- Exposure to CPG, retail, or consumer brand data (Nice to have).
- Experience with Spark, cloud platforms (AWS or similar), or orchestration tools (Nice to have).
- Familiarity with LLMs and their practical use in analytical workflows (Nice to have).
Skills
- Python
- SQL
- pandas
- scikit-learn
- Statistics
- Machine Learning
- Forecasting
- Optimization
- Anomaly Detection
- Measurement
- Experimental Design
- Backtesting
- Holdouts
- Error Analysis
- Feature Engineering
- Model Monitoring
- Spark (Nice to have)
- Cloud Platforms (AWS or similar) (Nice to have)
- Orchestration Tools (Nice to have)
- LLMs (Nice to have)
Location
- New York City
- Remote (U.S.)
Work Type
- Hybrid
- Remote
Experience Level
- Early career
Benefits
- Mentorship from Co-Founder & CAIO and senior engineers
- Scope for rapid growth
About the Company
- Sciemo builds AI for consumer goods, transforming data into measurable business impact.
- Our platform optimizes promotions and balances demand and supply using AI agents.
- We are an industry-leading startup developing AI for consumer brands.
- Our solutions leverage machine learning, generative AI, agent-based systems, and graph technologies.
- Headquartered in New York City.
Equal Opportunity
- We are an equal opportunity employer and consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law.
- We actively encourage diversity, inclusion, and equitable hiring practices.
- If you require accommodations during the hiring process, please reach out to our recruitment team at join@sciemo.ai.