Senior Data Scientist

The Role   

We are looking for senior-level Data Scientists to join our Data Engineering, Science, and Analytics team. Do you thrive at applying data science to solve business problems? As a data scientist, you will have ample opportunities to apply your data science skillset to unlock vast business opportunities by extracting key insights using a wide range of data sources, advanced statistical models, and machine learning algorithms and translating results into meaningful, goal-oriented business actions. Each day, you will be presented with a variety of new challenges and interesting projects that tap your interests and strengths. 

Responsibilities: 

• Collaborate with cross-functional partners in operations, finance, marketing, and engineering to understand business need and scope data science projects. 

• Wrangle, process, cleanse, verify, and enrich data from different sources used for analysis. 

• Help build data-informed business strategy and roadmaps. 

• Translate business needs into data product requirements, evaluate technologies, and identify opportunities to innovate and improve our data science capabilities. 

• Use creative problem-solving skills to analyze data and build statistical / machine learning models to help solve business problems from different perspectives. 

• Work closely with data engineers to create services that can ingest and supply data to and from both internal and external sources and ensure data quality and timeliness. 

• Lead the development of data visualization and dashboards to help the organization monitor performance, generate insights, and continuously improve user experience. 

• Establish playbooks to drive process and consistent outcomes. 

• Participating in the full life cycle of model development, which spans from business problem discovery, data discovery to model deployment and monitoring. 

Qualifications: 

• Master’s or Doctoral degree in Computer Science (with a focus on Data Mining, Machine Learning), Statistics, Econometrics, Physics, or other rigorous quantitative disciplines that require processing and modeling data at a complex and large scale. 

• 4+ years of professional experience as a data scientist. 

• Proficient in Python, SQL, Spark, the associated Python and Spark packages commonly used by data scientists, and Deep Learning libraries, such as PyTorch. 

• Proficient in data wrangling and exploratory analysis, with the ability to extract meaningful insights from complex datasets and establish robust data foundations for downstream modeling efforts. 

• Strong understanding of and practical experience in a wide range of machine learning algorithms and statistical modeling and inference. Experiences with Generative AI/ LLM application is a strong plus. 

• Experience and knowledge with computer vision domain, library such as OpenCV, PIL, and modern CV architectures (CNNs, Vision Transformers, Image Gen AI etc.) is preferred. 

• Experience in software development, system design and deployment is preferred. 

• Working experience in cloud-native technology. 

• Experience working with large structured and unstructured datasets stored in relational and NOSQL databases. 

• Out-of-the-box thinker and problem solver who can turn ambiguous business problems into clear data-driven solutions that deliver meaningful business impacts. 

• Excellent organizational skills, verbal and written communication skills, and presentation skills.