Join our team as a Data Engineer
At Alpha Tensor, we're seeking a skilled and driven Data Engineer to join our team. As a key player, you'll harness cutting-edge technologies, focusing on extracting insights from diverse datasets for advanced time-series forecasting. If you're passionate about exploring the depths of data and making a substantial impact, apply today to be part of our data-driven journey!
Location
Remote
Employment Type
Full-time
What You'll Do
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Strategize and execute the creation of extensive and diverse datasets, employing data augmentation techniques. Develop robust benchmarks and metrics to assess model performance, continuously refining methodologies. Address class imbalances through strategic sampling and fine-tune strategies for optimal results. Expertly engineer features to enhance dataset representativeness. Collaborate transparently, documenting processes to ensure reproducibility and driving innovation in cutting-edge data science solutions.
- We are looking for someone who is passionate about data and has a track record of developing successful predictive models. You should have a strong background in statistics, mathematics, and computer science, as well as experience working with large datasets. Additionally, you should be comfortable working in a fast-paced environment and collaborating with cross-functional teams.
Who You Are
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Holder of a BTech/BE in Computer Science, you bring valuable expertise, including:
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3 to 5 Years of Experience: Demonstrated proficiency in Python, serving as a key tool in your skill set, with 3 to 5 years of hands-on experience.
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Data Handling Experience: Previous experience working with datasets, showcasing your hands-on familiarity with diverse data types.
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Basic Machine Learning Understanding: A foundational understanding of machine learning concepts, laying the groundwork for further exploration and mastery.
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Statistical Prowess: Strong expertise in probability and statistics, essential for robust data analysis and modeling.
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Data Sampling Methodology: Adept at employing data sampling methodologies, showcasing your nuanced approach to handling data subsets.