Machine Learning Engineer
hace 6 meses
decision-making problems through constraint algorithms.
**Responsibilities**:
- Identifying and testing different machine learning strategies.
- Analyzing EV charging behavior and creating good models to predict several metrics such as capacity, parked time, arrival and departure times, etc.
- Analyzing and creating models for other types of data such as electricity prices and grid frequency.
- Using different metrics to compare the different strategies.
- Using data science and data analytics to compare and plot the results.
If you are someone who is driven by impact, thrives in a dynamic and collaborative work environment, and has a keen interest in contributing to the development of the optimization algorithm that powers the company, let's connect and chat
If you care about #sustainability & #climatechange and would like to make a difference with your software skills, we are looking for you
Kadre landed at #Barcelona to find a #Data Science (Machine Learning) to join an #energy startup
The startup has a cloud hosted algorithm that needs to connect to thousands of EV chargers in real time. Data needs to be collected, analyzed by our predictive models, fed into the optimization algorithm, and displayed in real time to users via our app. Long term storage is also necessary to store a variety of EV usage data points.
**Requisitos**:
**Technical requirements**:
- Proficiency in programming languages commonly used in data science and machine learning, such as Python. Familiarity with libraries and frameworks like NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch is a plus.
- Knowledge of a broad range of machine learning algorithms, such as regression, decision trees, random forests, support vector machines, neural networks, clustering, and dimensionality reduction techniques.
- Solid understanding of statistical concepts and mathematics, including probability, linear algebra, calculus, and hypothesis testing.
- Ability to clean, preprocess, and manipulate large datasets efficiently, extracting relevant insights and identifying patterns.
- Skill in using data visualization tools and libraries to present complex findings in a clear and understandable manner. Proficiency in libraries like Matplotlib,Seaborn, Plotly, Scikit Learn, Keras, etc. is valuable.
- Understanding of different evaluation metrics and techniques to validate the performance of machine learning models effectively.
- Ability to identify and engineer relevant features from raw data to improve model performance.
- Experience with version control systems like Git to manage codebase changes efficiently.
- Knowledge of working with SQL and databases to query, retrieve, and manage data. Experience using Pandas and NumPy to manage large scale datasets.
Beneficios
The position is not full remote, but will be highly flexible. Preferred hybrid work Employees have free access to DataCamp so they can upskill themselves About equity/bonus, the employee will have equity provided from an employee options pool. The employee will receive benefits according to the Spain regulations. Meaning, paid time off, sick leave, holidays, and the 13th and 14th salaries
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