As a Data Scientist, you will work with highly complex structured and unstructured datasets. Yes, we are talking terabytes. You will build Statistical, Machine Learning, and/or Deep Learning models to create solutions, improve operation, understand & interpret the data and be a building member of our SNS platform Yay!.
Responsibilities
- Collaborate with the product and engineering teams to define and design the recommendation engine’s architecture and algorithms
- Analyze user data to understand user behavior and preferences, enabling the development of personalized content recommendations
- Utilize statistical and machine learning techniques to analyze large datasets and derive actionable insights
- Conduct A/B testing to evaluate the effectiveness of recommendation algorithms and continuously refine the models
- Develop and implement machine learning models for content recommendation, personalized user experiences, and targeted content delivery
- Evaluate model performance and make data-driven adjustments to improve accuracy and relevance
- Prepare and preprocess raw data to ensure its suitability for analysis and modeling purposes
- Identify and address data quality issues to maintain the integrity of the recommendation engine
- Take a proactive approach in working closely with cross-functional teams, including (but not limited to) product managers, engineers, and designers, to align on data requirements and deliverables
- Communicate findings and insights effectively to technical and non-technical stakeholders
- Stay abreast of industry trends and advancements to propose innovative approaches and solutions
- Build state-of-the-art Deep Learning models to tackle Computer Vision and NLP problems
- Communicate with the stakeholders to understand the business problem, solve the problem using data, and effectively present the insights/results
Requirements
- 3+ years experience in data science: data visualization, regression, clustering and classification
- Fluent in Python (Numpy, Pandas, Scikit-Learn)
- Experience working with Machine Learning (Decision Trees, SVMs, Logistic Regression, PCA, Kernel Methods, LDA, QDA)
- At least 1 year working with Deep Learning. Being fluent in at least one DL framework (e.g. Tensorflow, Theano, Keras, MxNet, PyTorch, CNTK)
- Experience with data analytics
- Proficiency in SQL and MongoDB
- Can self-manage a project from start to finish and be proactive to propose projects that can provide fruitful insights
- B.S./M.S./PhD in mathematics, statistics, data science, computer science, electrical engineering, or related experience
- N1 level Japanese and have lived in Japan for more than 1 year.
Nice to haves
While not specifically required, tell us if you have any of the following.
- Experience working with big data
- Experience with parallel/distributed/cloud computing
- Experience training Deep Learning models on multiple GPUs
- Experience with generative AI
- Knowledge on (Deep) Reinforcement Learning
- Experience with unsupervised and generative models (e.g. Autoencoders and GANs)
- Experience with multi-task learning
Compensation
5 to 8 million JPY annually.
