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Data scientist/Machine learning engineer
1 week ago
Do you also want to make the world a little better while devoting yourself to cutting-edge technology development? Then Sigma Industry Development is the right company for you.
As a data scientist/machine learning engineer at Sigma Industry Development, you will:
1. Design solutions for distributed computing to handle large datasets
2. Develop domain expertise to better understand business problems and provide relevant solutions for the organization/client
3. Create clear and effective visualizations to present findings through visualizations and reports to non-technical stakeholders; communicating complex findings in a clear and understandable manner
4. Collaborate with cross-functional teams, including business analysts, engineers, and decision-makers
5. Apply critical thinking to frame and solve complex problems
6. Adopt an iterative approach to problem-solving, refining models based on feedback
7. Understand and adhere to data privacy and ethical considerations
8. Feature Engineering – Create and select relevant features to improve model performance
Welcome to the Sigma family. Your journey starts now, where each line of code etches a mark of your contribution on the canvas of our collective ambition.
Data Scientist/Machine Learning Engineer
Minimum Requirements
- M.Sc in Computer Science or Applied Physics/Mathematics
Experience
- At least five (5) years professional experience working as Data Scientist/Machine Learning Engineer
Know-how
- Data Analysis - Proficient in exploratory data analysis (EDA) to understand data patterns and trends.
- Statistical Modeling - Designing and implementing statistical models to derive insights from data.
- Hypothesis Testing - Conducting hypothesis testing to validate assumptions and make data-driven decisions.
- Programming Languages - Proficiency in programming languages such as Python or R for data manipulation and analysis; developing predictive models to forecast future trends and outcomes.
- Data Cleaning and Preprocessing - Cleaning and preprocessing raw data to prepare it for analysis.
- Data Wrangling - Manipulating and transforming data into a suitable format for analysis.
- Machine Learning and Algorithm Selection - Selecting appropriate machine learning algorithms based on the nature of the problem.
- Model Evaluation - Evaluating model performance using metrics like accuracy, precision, recall, and F1-score
- Feature Engineering - Creating and selecting relevant features to improve model performance
- Hyperparameter Tuning - Optimizing model hyperparameters for better performance
- Big Data Technologies - Familiarity with big data processing tools like Hadoop and Apache Spark
- SQL and NoSQL Databases - Proficiency in working with both SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB) databases.
- Swedish and English (spoken and written)
If the realm of AI holds a special place in your interests, consider it an added advantage. We're thrilled at the prospect of delving into the world of artificial intelligence alongside you. Together, we'll nurture and cultivate these skills, turning curiosity into expertise, and evolving with the ever-changing landscape of technology.
Apply today if you like to know more about Sigma Industry Development.
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