דרושים Data Scientist בכל הארץ

**Job Description

**At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.

**What We Do

**The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.

**Position Overview

**We are seeking experienced data scientists to create computationally intensive data science problems for an advanced AI evaluation project. This is a remote, project-based opportunity for experts who can design challenging problems that require computational methods to solve and mirror the full data science lifecycle - from data acquisition and processing to statistical analysis and actionable business insights.

What You'll Do

• Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare)
• Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn)
• Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
• Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction
• Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility
• Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency
• Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations)
• Incorporate big data processing scenarios requiring scalable computational approaches
• Verify solutions using Python with standard data science libraries and statistical methods
• Document problem statements clearly with realistic business contexts and provide verified correct answers

****Problem Domains (Examples)

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• Business Analytics & Predictive Modeling

• Customer segmentation, churn prediction, and CLV modeling algorithms

• Fraud detection with precision-recall optimization

• A/B test statistical calculations and experimental design

• Cohort analysis and retention rate computations

• Model evaluation metrics and performance optimization

• Statistical Analysis & Data Processing

• Hypothesis testing with multiple comparison corrections

• Causal inference: propensity score matching, difference-in-differences

• Complex ETL pipeline logic and multi-source data integration

• Missing data imputation and outlier detection algorithms

• Feature engineering: encoding, interactions, dimensionality reduction

• Time Series & Forecasting

• Trend decomposition and seasonality detection

• Stationarity testing and autocorrelation calculations

• Forecast accuracy metrics and moving average computations

• Optimization & Operations Research

• Resource allocation and constraint satisfaction problems

• Cost-benefit analysis and capacity planning optimization

• Network analysis and supply chain calculations

• Database & Mathematical Foundations

• Complex SQL query optimization and window functions

• Probability computations for business scenarios

• Linear algebra operations and matrix factorization

• Information theory metrics (entropy, mutual information)

• Optimization algorithms and convergence analysis

**Requirements

******Education & Core Experience

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• Advanced degree (Master's or PhD) in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field
• 5+ years of hands-on data science experience with proven business impact
• Portfolio of completed projects and publications showcasing real-world problem-solving

Technical Skills

• Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
• Statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
• SQL and database operations for data manipulation and analysis

****Modern AI/ML (Highly Valued)

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• Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
• Understanding of MLOps practices and model deployment workflows
• Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)

Professional Skills

• Ability to design problems reflecting real-world business scenarios and industry challenges
• Strong analytical and problem-solving skills with attention to detail
• Experience translating business requirements into technical solutions
• Clear technical writing and documentation skills
• Proficient in English for problem creation and communication

Preferred Qualifications

• Cross-industry experience (finance, telecommunications, healthcare, technology)
• Research background with publications or case studies
• Teaching, mentoring, or training experience
• Professional certifications in data science or machine learning

**Compensation

**Task-based compensation.

****Application Process

****Please submit:

• CV/Resume highlighting ML research or engineering background
• Domain knowledge test
• Python test
• 1-2 sample computational ML problems you've created (with solutions)
• Brief statement about your experience with computational ML problem-solving
• Interview