About the Role
Role details below.
Responsibilities
- Explore and analyze large volumes of data to gain insights and identify patterns relevant to modeling objectives
- Perform data cleaning, preprocessing, and transforming data into a suitable format for modeling
- Design and develop models using statistical and machine-learning techniques
- Select appropriate algorithms, perform feature engineering, model training, and evaluation
- Prepare data required for modeling, including gathering and integrating data from various sources
- Ensure data quality and consistency
- Define appropriate features and variables
- Assess the performance and accuracy of models using appropriate evaluation metrics
- Conduct experiments, cross-validation, and measure the effectiveness of recommendations
- Fine-tune models to optimize performance, improve accuracy, reduce bias or overfitting, and enhance algorithm efficiency
- Provide actionable recommendations
- Analyze large datasets to identify patterns, trends, and insights that can be leveraged to improve business performance
- Design, build and evaluate systems to personalize consumer experience and drive customer engagement
- Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions
- Conduct rigorous testing and validation of models to ensure their accuracy, robustness, and reliability
- Monitor model performance, identify areas of improvement, and continuously refine models based on new data and evolving business needs
- Stay up-to-date with the latest advancements in data science, machine learning, and recommendation system technologies
- Apply latest advancements in data science, machine learning, and recommendation system technologies to solve business challenges
Requirements
- Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Economics, Physics, or a related discipline
- 5+ years of experience working in a professional setting deploying models
- Strong experience in building and deploying into production predictive models and recommendation systems using statistical modeling, machine learning, and data mining techniques
- Deep experience with various machine learning techniques, such as regression, classification, clustering, dimensionality reduction, and ensemble methods
- Familiarity with popular algorithms like decision trees, random forests, Boosted trees, and regularized regression
- Experience with match-propensity models, embeddings based models, cold-start handling, calibration/post-processing, integrating models into ad-tech workflows and business logic, measuring model performance within ad-tech systems
- Solid foundation in statistical concepts, linear algebra, calculus, and probability theory
- Proficiency in programming languages such as Python or R
- Experience in data manipulation and analysis using libraries like NumPy, Pandas, or SciPy
- Solid understanding of data preprocessing, feature engineering, and model evaluation techniques
- Experience in ad-tech is a must
- Experience with media/advertising platforms, demand-side platforms and supply-side platforms in digital advertising or retail-media networks
Nice to Have
- Familiarity with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark)
Benefits
- Competitive compensation
- Flexible remote work
- Unlimited Responsible PTO
- Great opportunity to join a growing, cash-flow-positive company
- Direct impact on Nift's revenue, growth, scale, and future success
Compensation
Competitive compensation
Work Arrangement
Hybrid
Team
Reports to: Data Science Manager
Additional Information
- Company has experienced 731% growth over the last three years
- Backed by investors who supported Fitbit, Warby Parker, and Twitter
- Position is hands-on and involves applying expertise in statistical modeling, machine learning, and data mining techniques
- Role plays a crucial part in developing models for complex parts of the business
- Candidate will contribute to improvement and re-design of current models
