Data Scientist II
Role details
Job location
Tech stack
Job description
- Work on complex data science and analytics projects in support of the commercial organization.
- Develop data science models or algorithms independently and in collaboration with team members using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control and maintaining documentation of created applications.
- Work directly with customers and business partners to develop requirements and provide technical solutions through an analysis of business needs and pain points.
- Proactively assess current capabilities to identify areas for improvement, proposing solutions that align with core strategy and operation.
- Develop guidelines and standards for analytics, AI, and machine learning models, their deployment, and associated processes.
- Provides technical guidance or business process expertise, technical leadership, coaching and mentoring to team members.
Requirements
Two or more years of relevant experience in data science or related technical activities.
WE VALUE
Expert using scripting and querying languages, such as Python, SQL, and others. Python is preferred.
Demonstrated experience with Statistics, Machine Learning (Supervised & Unsupervised learning), and Deep Learning.
Demonstrated experience working with cutting edge analytics packages such as SciKit, TensorFlow, Matplotlib, Seaborn, PyTorch, GPT, PySpark, Bit bucket etc.
Knowledge of databases, data warehouse platforms (Snowflake) and Cloud based tools (Databricks)
Experience producing analytics data visualizations, preferably using Tableau, PowerBI, or equivalent.
Demonstrated experience in serving as a technical lead of moderately complex projects.
Demonstrated analytical skills, proficiency with computer software applications, and the ability to produce and consume written documentation.
Ability to understand a broad array of technical and business issues, prioritize work, and analyze issues to develop innovative and effective solutions.
Demonstrated initiative staying current on industry practice outside of study and training.
Ability to effectively lead team interaction, including meetings and collaboration, to resolve issues.
Proven mentoring ability to drive results and technical growth in peers.
Effective communication skills (verbal, written, and presentation) for interacting with customers and peers.
Demonstrated application of statistics, statistical modeling, and statistical process control.
User experience mindset, including the generation of insights to drive visualizations and infographics to distill complex information.