Data Scientist

Job Description

Responsibilities
Drive the design and enhancement of data-centric products to boost user productivity, streamline processes, and support strategic decision-making while reducing operational costs.
Integrate and transform diverse internal and external datasets to engineer robust features that enable advanced analytics and machine learning.
Design and implement sophisticated statistical models and machine learning algorithms to analyze large-scale data.
Plan and conduct rigorous data-driven experiments to validate hypotheses and measure the impact of business initiatives.
Develop intuitive data visualizations and dashboards to communicate insights effectively to both technical and non-technical audiences.
Automate repetitive data workflows using Python and SQL to improve efficiency and reduce errors.
Apply Natural Language Processing (NLP) and Large Language Models (LLMs) to analyze unstructured text data and automate content-related tasks.
Deploy machine learning models using Databricks, ensuring seamless integration with existing data workflows and real-time decision systems.
Design and maintain scalable and reliable data pipelines to support machine learning and analytics workloads for large datasets.
Utilize simulation, optimization, and distributed computing techniques to efficiently manage large datasets and improve processing.
Use clustering, classification, and regression techniques to extract actionable insights and solve complex problems.
Leverage libraries such as Pandas, NumPy, and SQLAlchemy to build robust ETL pipelines and maintain data consistency.
Desired Candidate Profile

Bahraini, Indian

Bachelors in Computer Application(Computers), Bachelor of Technology/Engineering(Computers), Bachelor of Science(Computers)

Any

Education Requirements

Bachelor’s degree in Computer Applications, Economics, Statistics, Mathematics, or a related quantitative discipline.

Essential Technical Skills

Python: Advanced expertise in Python for building machine learning models, developing backend systems, and constructing scalable data pipelines.
Natural Language Processing (NLP): Strong proficiency in NLP methods for analyzing unstructured text data and extracting meaningful insights.
SQL: Solid command of SQL for managing, querying, and analyzing large datasets, especially within cloud-based infrastructures.
Cloud Computing: Hands-on experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure to deploy machine learning solutions and data applications in scalable and secure environments.

Key Soft Skills

Excellent analytical and problem-solving abilities with a strategic mindset.
Strong communication skills, capable of translating complex technical concepts into clear language for non-technical stakeholders.
Collaborative team player who works effectively across data, engineering, and business units to deliver end-to-end solutions.
Meticulous attention to detail and a commitment to building robust, high-performance systems.
Adaptable and open to Agile methodologies, capable of thriving in dynamic, fast-paced environments with multiple stakeholders.
Open-minded and eager to learn, with the ability to work effectively alongside analysts, business partners, and technical teams.