Data Scientist II

## To be a family that uses our collective superpowers to do significant good. **Master Electronics** has an exciting career opportunity for a **Data Scientist**. As a **Data Scientist**, you'll be a key contributor in designing, building, and evaluating data-driven decision systems, with a strong emphasis on pricing optimization, experimentation (A/B testing), and causal analysis that directly influence product and business outcomes. ## What you will do? - Design, build, and refine pricing and optimization models, including dynamic pricing, price elasticity estimation, margin optimization, and demand forecasting, that directly drive revenue and profitability decisions - Own the experimentation lifecycle: design and run A/B and multivariate tests, define success metrics and guardrails, determine sample sizes and test duration, analyze results with statistical rigor, and communicate causal impact to stakeholders - Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible - Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and deployment - Develop scalable data pipelines on Databricks; integrate experimentation and ML systems with modern data and MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability - Partner with software engineers, data engineers, product managers, and subject-matter experts; present insights and recommendations to technical and non-technical stakeholders; translate complex analyses into clear narratives - Research and apply emerging ML techniques; contribute to improving team standards and mentoring junior team members ## What you bring to the table! - 3-5 years of professional experience as a data scientist or ML engineer, with a proven record of buildingand deploying ML models in production - Hands-on experience with pricing, revenue, or marketing optimization, such as price elasticity modeling,dynamic pricing, promotion optimization, or mathematical optimization methods - Demonstrated expertise in A/B testing and experimentation: hypothesis design, power analysis, sequentialtesting, guardrail metrics, and interpreting results under real-world constraints (novelty eff ects,interference, heterogeneous treatment eff ects)Hands-on Databricks experience for building and deploying data science workloads at scale - Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or arelated quantitative fi eld, or a Bachelor's degree with 5+ years of equivalent professional experience - Strong programming skills in Python (plus experience in JavaScript), with profi ciency in ML libraries (scikit-learn, PyTorch), data manipulation (pandas, SQL), and statistical analysis - Solid grounding in statistics: hypothesis testing, confi dence intervals, regression, and Bayesian methods - Knowledge of MLOps tools and cloud platforms, especially Databricks (Spark, MLfl ow), AWS (S3,Redshift, SageMaker), or similar services - Excellent communication skills; ability to explain complex technical concepts to both technical andbusiness audiences and to collaborate eff ectively across teams - Demonstrated ability to work independently on complex problems, manage multiple projectssimultaneously, and deliver results in a fast-paced environment**Preferred Qualifications** - Advanced degree (Master's or PhD) in a relevant fi eld (Statistics, Machine Learning, AI, OperationsResearch, Economics/Econometrics, etc.) - Experience with B2B or ecommerce pricing, such as quote optimization, contract pricing, or price-listmanagement in a distribution or catalog business - Familiarity with experimentation platforms (in-house or commercial, e.g., Optimizely, Statsig, GrowthBo…