MPB customers come from all walks of life, and so do we. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant because of family makeup, race, sexuality, religion, gender identity, disability or age. At MPB, every employee has the opportunity to make an impact and grow. The Opportunity: In this role, you will be working alongside the Senior Data Scientist to scale and elevate our current and future Data Science Data Products.
Key Responsibilities:
- Immerse yourself in our Pricing Optimization model approach. Contribute to improvements, troubleshoot, and maintain the end-to-end process.
- Hands-on machine learning model development, considering data gathering nuances when making modeling and data processing choices.
- Own and enhance our Data Science products, suggesting techniques, feature engineering, and deployment improvements while collaborating within a modern DS team using JIRA and version control best practices.
- Explore new Data Science opportunities, conducting experiments and adapting approaches to ensure scalability and deliverability.
- Produce accessible outputs from ML products, including concise presentations of findings, designing Tableau dashboards, delivering batch predictions, or building API endpoints for online inference.
Who you are:
- A theoretical background in Data Science techniques with broad understanding of common approaches.
- Some commercial experience with the eagerness to learn and adapt in a fast-paced environment, applying critical thinking, design thinking, and pragmatism.
- A proactive individual who takes ownership of projects, bringing creativity, flexibility, and enthusiasm to enhance deliverables.
Required Skills:
- Solid understanding of Data Science techniques and their appropriateness for various business problems.
- Good competency in Python and SQL; familiarity with working with Python and data (e.g., virtual environments, scripts, Jupyter notebooks, local vs cloud) desirable.
- Competency in software engineering techniques, including version control, CICD, and software design patterns.
- Familiarity with ML packages such as scikit-learn and XGBoost; experience in deep learning (e.g., Pytorch or TensorFlow) beneficial but not required.
- Relentless appetite to learn and adapt techniques to business context, prioritizing value in approach selection.
- Familiarity with GCP or alternatives like AWS, with bonus points for familiarity with MLOps elements like Vertex and Cloud Functions.
- Good understanding of end-to-end deployment and management of Data Science products, with experience in production DS products beneficial.
- Excellent communication skills, able to present project outputs to varied audiences and influence stakeholders effectively.
Please use the below link for job application and quicker response: Apply Here.
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