Boxy Charm is seeking a highly motivated individual responsible for driving intelligent solutions and recommendations for the company.
The Data Scientist will use a range of data science and machine learning methodologies to build solutions for a variety of business initiatives. Additionally, the ideal candidate will be able to solve complex problems and apply those solutions within a cutting-edge cloud-based technology platform.
The role will be filled with a solution-oriented candidate that thrives on working in a highly dynamic and engaging environment.
Essential Duties and Responsibilities
- Work closely with different business units and translate high level business problems into actionable deliverables for the Data & Algorithms team
- Work with a wide variety of data ranging between social media and email to customer transactions and logistics
- Develop a variety of machine learning models including customer recommendations, customer propensity, forecasting, and marketing performance.
- Collaborate closely with the Software Development and DevOps teams to ensure continued delivery of high quality data through our data processing pipeline
- Partner with various business stakeholders and implement solutions that improve their business process
- Conduct big data analysis using SQL, Python, Snowflake, Spark and other technologies
- Break down complex projects and problems into actionable tasks that be delivered quickly and iteratively and provide value to the business stakeholders
- Customer lifetime value, regression analysis, cohorts, retention, customer lifecycle, customer segmentation, machine learning, large-scale data analysis, classification and propensity modeling
Education and/or Experience
- Bachelor's degree or higher in Computer Science, Math, Statistics or a related field
- 3+ years of experience programming in languages such as Python, Java, Scala, Ruby, R
- 3+ years of experience working with SQL and relational databases
- 3+ years of experience with machine learning, statistical modeling, and data mining techniques
- Experience with one or more machine learning algorithms such as neural networks, regression, clustering etc.
- Working experience with machine learning technologies such as TensorFlow, Keras, ScikitLearn, H20.ai, MXNet, Caffe, Gluon etc. is highly desirable
- Experience working in an Agile (SCRUM, XP etc.) development environment
- Experience with AWS or other cloud environments is desirable
- Knowledge of Big Data and NoSQL systems such as Snowflake, Hadoop, Spark, MongoDB, etc. is a plus