Data Scientist

1 week ago

Doha, Qatar Nair System Full time

Nair Systems is currently looking for Data Scientist for our Qatar operations with the following terms & conditions.

**Requirements**:

- Minimum of 5 years of professional experience as a Data Scientist, with a focus on machine learning, AI, and data analysis in the banking sector, specifically in mobile banking and internet banking.
- Strong expertise in developing and implementing machine learning algorithms, such as
- regression, classification, clustering, time series analysis, recommendation systems, and natural language processing (NLP), to solve real-world business problems.
- Proficiency in programming languages such as Python or R, along with experience working with
- machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data manipulation tools (e.g., pandas, NumPy).
- Solid understanding of statistical analysis, experimental design, hypothesis testing, and data visualization techniques. Ability to effectively communicate complex analytical concepts and results to technical and non-technical stakeholders.
- Experience in working with big data technologies (e.g., Hadoop, Spark) and cloud-based
- platforms (e.g., AWS, Azure, GCP) for data storage, processing, and analysis.
- Familiarity with data preprocessing techniques, feature engineering, and data quality
- assessment to ensure robust and reliable model performance.
- Strong problem-solving skills, with the ability to identify business challenges, frame them into analytical problems, and develop innovative data-driven solutions.
- Excellent communication and collaboration skills, with the ability to work effectively in crossfunctional teams and present findings to stakeholders at various levels of the organization.
- Bachelor's degree in Computer Science, Statistics, Data Science, or a related field. A Master's or Ph.D. degree in a relevant discipline is highly desirable

**Responsibilities**:

- Develop and implement advanced machine learning and AI algorithms and models to drive insights and solutions for banking-related challenges, such as customer segmentation, fraud detection, risk assessment, and personalized recommendations.
- Collaborate with cross-functional teams, including data engineers, business analysts, and product managers, to identify and define business problems, develop data-driven solutions, and translate them into actionable recommendations.
- Design and build scalable and efficient data pipelines, data preprocessing workflows, and data integration processes to ensure the availability of high-quality data for analysis and model development.
- Stay up-to-date with the latest advancements in machine learning, AI, big data technologies, and innovative solutions in the banking industry. Evaluate and recommend the adoption of new tools, frameworks, and methodologies to enhance data analysis and predictive modeling capabilities.
- Conduct in-depth exploratory data analysis to identify patterns, trends, and anomalies in the data. Communicate findings effectively to stakeholders and provide actionable insights to drive informed decision-making.
- Collaborate with stakeholders to define key performance indicators (KPIs) and develop
- predictive and prescriptive models to optimize business operations, customer experience, and marketing strategies in the banking domain.
- Ensure the ethical use of data and maintain compliance with regulatory requirements, data privacy, and security standards within the banking industry.

Joining time frame: 2 weeks (maximum 1 month)

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