Employment Information
Are you ready to bring your Data Science experience to the next level?
As a Data Scientist specializing in Machine Learning, you’ll play a crucial role in developing and implementing cutting-edge recommendation algorithms. Your expertise will help drive user engagement, enhance customer experiences, and contribute to the growth of the company. You’ll work closely with a talented cross-functional team to turn data into actionable insights that drive our recommendation platforms forward.
Key Responsibilities:
- Collaborate with the product team to understand user needs, business objectives, and industry trends;
- Develop and implement state-of-the-art machine learning algorithms for recommendation systems;
- Collect, preprocess, and analyze diverse datasets to extract meaningful insights and patterns;
- Build and optimize recommendation models, leveraging techniques such as collaborative filtering, content-based filtering, and deep learning;
- Implement experiments and A/B tests to evaluate and enhance the performance of recommendation algorithms;
- Work closely with engineers to deploy and maintain recommendation models in production environments;
- Create intuitive data visualizations and reports to effectively communicate insights to team members and stakeholders;
- Stay informed about the latest advancements in recommendation systems, machine learning, and related technologies;
- Contribute to a collaborative startup culture by sharing knowledge and insights with fellow team members;
- Adapt and thrive in a fast-paced, evolving environment typical of startup companies.
Qualifications and Skills:
- Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field;
- Demonstrated experience in designing and implementing recommendation algorithms in real-world applications;
- Proficiency in programming languages such as Python or R for data manipulation and machine learning;
- Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, scikit-learn, etc.;
- Knowledge of deep learning techniques and frameworks for building recommendation models is a plus;
- Strong understanding of data preprocessing, feature engineering, and model evaluation;
- Experience with A/B testing methodologies and experimental design;
- Excellent problem-solving skills and ability to thrive in a dynamic startup environment;
- Effective communication skills to convey complex technical concepts to both technical and non-technical stakeholders;
- Collaborative mindset and willingness to work closely with cross-functional teams;
- Previous experience in startups or entrepreneurial environments is advantageous.
Benefits:
- Competitive compensation package with equity options;
- Flexible work environment that values work-life balance;
- Opportunity to work on cutting-edge technologies and shape the future of recommendation systems;
- Collaborative and inclusive startup culture that encourages innovation and creative problem-solving;
- Growth opportunities and the chance to take on additional responsibilities as the company expands.
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