We are seeking an experienced Data Scientist to join our growing team. In this role, you will leverage advanced analytics, machine learning, and statistical modeling to drive business performance improvements and cost efficiencies. The focus is on developing data‑driven solutions for pricing optimization, operational analytics, and predictive modeling that deliver measurable impact.

This organization is a rapidly growing data product company that partners with enterprise‑level clients across a variety of industries. The mission is to deliver digital solutions that accelerate growth by creating value through innovation.

Key Responsibilities

Data Analysis and Research: Analyze large datasets using advanced statistical techniques, extract insights, and produce actionable recommendations for pricing strategies and operational improvements.
Predictive Modeling: Develop and validate machine learning models for pricing optimization, demand forecasting, competitor behavior prediction, and operational efficiency enhancement.
Experimentation and Causal Inference: Design A/B testing frameworks, analyze results, and provide reliable insights for strategic decision‑making.
Advanced Analytics: Build sophisticated pricing models, analyze price elasticity, develop dynamic pricing strategies, identify cost‑reduction opportunities, predict maintenance needs, and apply advanced statistical methods (regression analysis, time‑series forecasting, market elasticity modeling).
Collaboration: Partner with business stakeholders, ML engineers, and product teams to translate analytical findings into actionable strategies.

Additional Responsibilities

Business Acumen: Strong understanding of how data science drives business value and ROI.
Analytical Rigor: Commitment to statistical best practices and scientific methodology.
Communication: Ability to clearly present complex findings to both technical and non‑technical audiences.
Problem‑Solving: Skilled at framing business challenges as analytical questions and developing appropriate methodologies.
Innovation: Proactive in identifying new opportunities for data‑driven solutions.

Basic Qualifications

Master’s degree in Data Science, Statistics, Economics, Mathematics, or a related quantitative field.
3+ years of professional experience in data science, analytics, or quantitative research.
Proven ability to define business questions, extract insights from large datasets, and deliver data‑driven recommendations.
Strong verbal and written communication skills with experience presenting analytical results to varied audiences.
Expertise in experimental design, hypothesis testing, A/B testing, and causal inference methods.
Advanced knowledge of statistical techniques (regression modeling, time‑series analysis, econometric methods).
Deep understanding of machine learning algorithms (supervised/unsupervised learning, ensemble methods, deep learning) and their applications.
Proficiency in Python or R for statistical analysis and machine learning, with strong SQL skills for data manipulation.
Experience with data visualization tools and techniques for communicating insights.

Additional Qualifications

Experience with pricing analytics, revenue optimization, or market research.
Knowledge of econometric modeling and price elasticity analysis.
Familiarity with AWS cloud platform and big data technologies.
Experience with experimentation platforms and statistical software packages.
Background in retail, energy, or operations analytics.
Knowledge of natural language processing for conversational AI applications.

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