- Design develop and deploy machine learning models to solve business problems across product marketing and operations.
- Extract clean and transform large-scale datasets from diverse sources using SQL Python and cloud-based data platforms.
- Conduct exploratory data analysis (EDA) to identify trends anomalies and opportunities for optimization.
- Build and maintain scalable data pipelines and automated workflows using tools like Apache Airflow Spark or AWS Glue.
- Collaborate with engineers to integrate models into production systems and ensure model performance reliability and monitoring.
- Communicate complex technical findings and insights clearly to non-technical stakeholders through visualizations and reports.
- Stay current with emerging trends in data science AI and machine learning and apply innovative techniques to real-world challenges.
- Participate in the full lifecycle of data projectsfrom ideation and experimentation to deployment and evaluation.
Requirements
- Bachelors or Masters degree in Computer Science Statistics Mathematics Data Science or a related quantitative field.
- 25 years of hands-on experience in data science machine learning or a related role within a technology-driven organization.
- Proficiency in Python SQL and data manipulation libraries (e.g. Pandas NumPy).
- Strong understanding of machine learning frameworks (e.g. Scikit-learn TensorFlow PyTorch) and model evaluation techniques.
- Experience with big data technologies such as Spark Hadoop or cloud platforms (AWS GCP or Azure).
- Familiarity with version control (Git) CI/CD pipelines and containerization (Docker Kubernetes) is a plus.
- Excellent problem-solving skills attention to detail and ability to work independently and in agile teams.
- Strong communication skills with the ability to translate technical concepts into business value.
- Prior experience in building and deploying ML models in production environments is highly desirable.
Required Skills:
Career in software testing
Required Education:
(CSE IT)
Design develop and deploy machine learning models to solve business problems across product marketing and operations.Extract clean and transform large-scale datasets from diverse sources using SQL Python and cloud-based data platforms.Conduct exploratory data analysis (EDA) to identify trends anomal...
- Design develop and deploy machine learning models to solve business problems across product marketing and operations.
- Extract clean and transform large-scale datasets from diverse sources using SQL Python and cloud-based data platforms.
- Conduct exploratory data analysis (EDA) to identify trends anomalies and opportunities for optimization.
- Build and maintain scalable data pipelines and automated workflows using tools like Apache Airflow Spark or AWS Glue.
- Collaborate with engineers to integrate models into production systems and ensure model performance reliability and monitoring.
- Communicate complex technical findings and insights clearly to non-technical stakeholders through visualizations and reports.
- Stay current with emerging trends in data science AI and machine learning and apply innovative techniques to real-world challenges.
- Participate in the full lifecycle of data projectsfrom ideation and experimentation to deployment and evaluation.
Requirements
- Bachelors or Masters degree in Computer Science Statistics Mathematics Data Science or a related quantitative field.
- 25 years of hands-on experience in data science machine learning or a related role within a technology-driven organization.
- Proficiency in Python SQL and data manipulation libraries (e.g. Pandas NumPy).
- Strong understanding of machine learning frameworks (e.g. Scikit-learn TensorFlow PyTorch) and model evaluation techniques.
- Experience with big data technologies such as Spark Hadoop or cloud platforms (AWS GCP or Azure).
- Familiarity with version control (Git) CI/CD pipelines and containerization (Docker Kubernetes) is a plus.
- Excellent problem-solving skills attention to detail and ability to work independently and in agile teams.
- Strong communication skills with the ability to translate technical concepts into business value.
- Prior experience in building and deploying ML models in production environments is highly desirable.
Required Skills:
Career in software testing
Required Education:
(CSE IT)
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