We are a premier Business and Technology Services provider offering innovative business solutions and Talent acquisition strategies to employers of all sizes, including Fortune 1000 companies and many large Private and Public-Sector organizations in the areas of Information Technology, Software Engineering, Manufacturing, Supply Chain, Finance, Telecom, Engineering, HR and many others.

Must Have requirements:

1. Master degree in computer science or data science
2. 2 years professional experience as software development engineer, data scientist, or machine learning engineer
3. Proficient in Python, with solid background in data structures and algorithms
4. Experience with computer vision

Responsibilities:
• Applies machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within PG&E’s software development environment. 
• Gathers, cleans, transforms, and/or reduces data from dissimilar sources from across PG&E. 
• Collaborates with team members and stakeholders to effectively manage the lifecycle of a model, retraining, replacing or sunsetting models when appropriate. 
• Shares and collaborates with other PG&E data scientists. • Delivers best-in-class software as part of a software delivery team.

Duration: 8 months 

Qualifications:
Minimum Education/Skills: 
• Bachelor’s Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience 
• Job-related experience, 5 years, OR Master’s Degree and job-related experience, 3 years, OR Doctorate 

Desired Education / Skills: 
• Experience with the data science lifecycle, including data engineering, feature engineering, model building and evaluation, model deployment. 
• Knowledge of commonly used data science programming languages, packages, and tools, especially Python. 
• Understanding of data science/machine learning models and algorithms, not limited to: deep learning (CNN, RNN etc), decision trees (e.g. xgboost, random forest), unsupervised techniques (e.g. clustering, anomaly detection), natural language processing and statistical methods. 
• Experience training models in a public cloud environment, using tools such as Jupyter, AWS Sagemaker. 
• Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. 
• Ability to clearly communicate complex technical details and insights to colleagues and stakeholders. 
• Knowledge of the mathematical and statistical fields that underpin data science • Knowledge of systems thinking and decomposition of complex problems. 
• Humble – is open to being coached, has high EQ and is self-aware • Hungry – desires to get things done while honoring people, and seeks better ways to do the job 
• Collaborative – has strong interpersonal skills; cares about and works well with teammates 
• Experience working on an agile delivery team, using methods such as Scrum, Kanban.

All your information will be kept confidential according to EEO guidelines.