Data Sciencist en remoto

Descripción del puesto de trabajo

Plants of Tomorrow (PoT) is a strategic program from our Client multinantional swiss, having the goal to empower their business to increase productivity, reduce costs and get insights for new innovation by using Artificial Intelligence and Machine Learning onsite and in real time.

PoT ML-OPS culture of diversity, intellectual curiosity, problem solving, and innovation oriented towards helping solving business problems and openness is key to its success. Our team brings together people with a wide variety of backgrounds, experiences and perspectives.

Key Responsibilities:

Drive autonomously multiple developments and/or deployments across various products to meet organization’s objectives.
Work with business stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop, deploy and maintain custom data models and algorithms to apply to data sets.
Use predictive modeling to increase and optimize manufacturing processes, product quality and other business processes.
Develop testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.
Develop processes and tools to monitor and analyze model performance and data accuracy.

Key Values:

Self-driven, autonomous, results oriented person
Enjoys solving business and technical challenges
Positive and joyful attitude including under stress
Analytical and practical mindset
Curiosity to explore
Design solutions considering the context
Build solutions to be reliable, secure, sustainable and performant while remaining pragmatic in achieving the intermediate objectives
Courage to take risks
Perseverance in face of setbacks

Key Skills:

Strong problem solving skills with an emphasis on product development.
Knowledge of a variety of machine learning techniques (time series, regression, classification, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (forecasting, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques.
We’re looking for someone with 7-10 years of experience manipulating data sets and building statistical and machine learning models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
Expertise in coding, algorithms, and proficiency in any of these programming languages: Python, R, Scala, C++.
Experience querying databases and using statistical computer languages to manipulate data and draw insights from large data sets: SQL, Python, etc.
Experience using major cloud providers (for machine learning training / MLOps pipelines) like GCP, AWS, Azure, etc.
Experience using AutoML tools, such as: DataRobot, Vertex AI, etc.
Experience working in the MLOps setup, deploying and scaling multiple products.
Adequate expertise and experience in delivering solutions to production via Continuous Integration/Continuous Delivery (CI/CD).
Experience creating and using advanced machine learning algorithms and statistics: time series, regression, simulation, scenario analysis, modeling, clustering, anomaly detection, decision trees, neural networks, etc.
Experience visualizing/presenting data for stakeholders using: Google DataStudio, Tableau, Qlik, Plotly/ggplot/Matplotlib.
Advanced/bilingual English essential, the interviews will be conducted in this language, other languages such as French or German are valuable

Tecnoempleo