RESPONSIBILITIES:
•Collect and analyze large datasets from diverse sources to drive key business insights.
•Develop machine learning models, including supervised and unsupervised learning techniques, to predict and optimize business outcomes.
•Implement and optimize deep learning architectures and algorithms such as neural networks and reinforcement learning.
•Construct data architectures, models, and protocols to identify trends and insights.
•Create visualizations and dashboards to present data insights to stakeholders clearly and effectively.
•Work collaboratively with cross-functional teams to integrate machine learning insights into business strategies.
•Manage projects independently and provide guidance to junior professionals.
•Stay updated with the latest trends and advancements in machine learning and data science, applying them as needed.
REQUIRED SKILLS AND QUALIFICATIONS:
Education Requirements:
•Solid educational background in mathematics, computer science, statistics, economics, or related fields.
Experience Requirements:
•Proven 3+ years of experience as a Data Scientist or in similar role
•Proficient in programming languages such as Python and R, with a strong emphasis on machine learning libraries (e.g., scikit-learn, TensorFlow, Keras, PyTorch).
•Strong understanding of machine learning algorithms, including regression, classification, clustering, and dimensionality reduction techniques.
•Experience with deep learning frameworks and building complex neural network models.
•Expertise in natural language processing (NLP) techniques and applications.
•Proficiency in data visualization tools like Tableau or Power BI, and ability to communicate findings effectively.
•Strong data manipulation and database management skills, including SQL.
•Analytical thinking and problem-solving skills with the ability to develop innovative solutions.
•Strong business acumen and ability to translate machine learning insights into actionable business strategies.
•Excellent communication and interpersonal skills for effective collaboration with stakeholders.
•Experience with cloud platforms such as AWS, Azure, or Google Cloud for deploying machine learning models is a plus.
•Knowledge of AutoML platforms and emerging technologies like generative AI.
•Proficiency in English (both spoken and written)
