Descrição
Mid Data Science Engineer (m/f) – Remote
Match Profiler is an Information Systems consultant who has been working in the national and international market since 1999. We have multidisciplinary skills and IT know-how that allow us to contribute, optimize, and progress with our clients. We are currently recruiting for integration into our internal team/client, professionals with the following profile:
What do you need to have:
- Hard Skills:
- Bachelor's/Master´s degree in a relevant field, PhD preferred
- Minimum 3 years of experience
- Solid knowledge of designing and implementing Machine Learning models and algorithms to solve complex business problems
- Experience with machine learning packages like scikit-learn, TensorFlow, etc.
- Working with large datasets to derive actionable insights
- Proficiency in languages like Python or R
- SQL knowledge
- Experience with cloud-based AI/ML and data analytics tools such as AWS, GCP, Azure
- Data visualization skills using tools like Tableau or PowerBI
- Understanding of the end-to-end Machine Learning Lifecycle (including model deployment) (plus)
- Experience with Recommendation Systems, Time series and forecasting analysis, Clustering, Language models, Computer Vision (plus)
- Familiarity with Big Data technologies such as Hadoop, Spark, etc. (plus)
- Familiarity with DevOps principles (plus)
- Good domain knowledge, enabling better understanding of data and business needs (plus)
- Soft Skills:
- Good communication
- Team spirit
- Proactivity
- Time management
- What we can offer:
- Personalized support from your team
- Your manager will take into consideration your motivations and suggestions
- Victories will be celebrated together
- Your HR and Support Teams will always be available to help
- Constant feedback on your work
- A network of hundreds of partnerships with companies from numerous sectors that offer you exclusive discounts (health, well-being, travel, gastronomy, culture, leisure, training, etc.)
- And, of course, many gatherings and social events
- #J-18808-Ljbffr
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