The Strategic Technology Data Science Intern will support the development of new analysis and prediction tools.
Essential Job Functions:
- Acquire and process market and operational data into proper form for machine learning and optimization algorithms to use.
- Improve automation of data acquisition, model training, and model testing processes in AWS and on-premise.
- Develop strong Domain Knowledge regarding power markets.
- Apply theoretical and practical knowledge of statistical analysis and machine learning techniques and tools to solve business problems.
- Other projects as assigned.
- Core Competencies:
Self-Starter – The Strategic Technology Data Scientist shall work effectively and efficiently with little oversight. He/she is a self-starter showing a strong bias for action with a sense of urgency and high energy. The Strategic Technology Data Scientist works within a collaborative environment to achieve improved results.
Uses Effective Communication Skills – The Strategic Technology Data Scientist uses effective communication skills to manage communication and feedback within the organization. He/she is candid, clear, and concise in communication. He/she effectively matches style, tone, and delivery method of the intended audience.
Problem Solving – The Strategic Technology Data Scientist has strong problem-solving skills, can research and troubleshoot issues and propose and implement solutions.
Displays Leadership/Team Orientation – The Strategic Technology Data Scientist displays leadership and team orientation by working collaboratively to achieve the organization’s success. He/she effectively practices a high level of good judgment and interpersonal skills.
Technical Skills – The Strategic Technology Data Scientist holds him/herself and others to high technical standards.
Knowledge, Skill, and Abilities:
- Strong background in data mining and statistical analysis.
- Experience with data preparation, data cleansing, SQL, and workflow/ETL tools like Knime.
- Strong understanding of optimization theory, along with related algorithms and tools.
- Experience with machine learning data preparation concepts (cross validation, folding, boosting, feature engineering) with clear understanding of time series related concerns.
- Experience with machine learning algorithms and frameworks, including Tensorflow, PyTorch, XGBoost, LightGBM and API wrappers like Keras.
- Experience with implementing and evaluating models to solve classification and regression tasks using models based on architectures like LSTM networks, CNNs, and GBDTs.
- Able to quickly learn necessary skills and information to be effective in position where necessary.
- Curious, inquisitive, creative and self-motivated with a passion for applied Machine Learning and optimization.
Physical Requirements and Working Conditions:
The job will require sitting in an indoor office environment, the need to visually read various written materials including, but not limited to paper documents and computer monitors. The job may also require standing, bending, walking, lifting up to 10 lbs., carrying, pushing, pulling, climbing, kneeling, and crouching.
The incumbent will have the ability to use standard office equipment such as PC, printer, telephone, calculator, and copy and fax machines.
Tenaska is an equal opportunity employer.