ఎ
Data Science Specialist
Mississauga, Ontario, Canada · ఒప్పందం
దరఖాస్తు చేసుకునే వారిలో మొదటి వ్యక్తిగా ఉండండి
- అనుభవం
- 5+ సంవత్సరాలు
- జీతం
- —
- ఖాళీలు
- 1
- పోస్ట్ చేయబడింది
- 12 గంటల క్రితం
- పని విధానం
- కార్యాలయంలో
- విద్య
- బ్యాచిలర్ డిగ్రీ
- పునఃప్రారంభం
- దరఖాస్తు చేసుకోవాలి
మీరు ఎక్కడ పని చేస్తారు
ఉద్యోగ వివరణ
Overview
Artech L.L.C. is seeking a skilled Data Science Specialist to join their team in Mississauga, Ontario in a hybrid work setting. This role focuses on transforming complex data into practical insights and advancing AI, machine learning, and generative AI projects that foster tangible business benefits.
Key Responsibilities
- Analyze extensive datasets, both structured and unstructured, to detect trends, patterns, and business insights.
- Conduct data cleansing, transformation, and feature engineering to facilitate advanced analytics and machine learning models.
- Design, test, and maintain predictive and prescriptive models using statistical and machine learning methods.
- Collaborate with technology teams to implement analytical solutions and machine learning models in production environments.
- Manage the full machine learning lifecycle involving model development, training, testing, monitoring, validation, and performance assessment.
- Work with business, technology, and risk stakeholders to convert complex challenges into data-based solutions.
- Document methodologies, assumptions, and outcomes to support oversight and review processes.
- Effectively communicate analytical findings and project progress to both technical and non-technical audiences.
- Keep abreast of emerging technologies such as machine learning, deep learning, large language models, and generative AI.
Qualifications
- Bachelor’s or master’s degree in computer science, data science, statistics, mathematics, engineering, or another related quantitative discipline.
- At least 5 years of experience in data science, machine learning, advanced analytics, or related fields.
- Proven experience in creating, validating, and evaluating machine learning models.
- Strong grasp of machine learning and deep learning methodologies and best practices for model development.
- Proficiency with programming languages and frameworks such as Python, SQL, Spark, PySpark, and TensorFlow.
- Knowledge of large language models and generative AI technologies.
- Excellent analytical reasoning, problem-solving abilities, and communication skills.
- Capable of working independently and collaborating effectively with multidisciplinary teams.