We are looking for a highly-skilled Data Scientist to join our team and play a pivotal role in transforming raw data into actionable insights. The ideal candidate is passionate about leveraging data to solve real-world business problems, possesses a strong analytical mindset, and is comfortable working in a dynamic, fast-paced environment.
Data Analysis & Interpretation: Analyze large datasets to discover trends and patterns that help drive business strategies and decision-making.
Predictive Modeling: Build and deploy machine learning models to forecast business outcomes, customer behavior, and operational improvements.
Data Collection: Collaborate with internal teams to gather, clean, and preprocess data from multiple sources.
Statistical Analysis: Use advanced statistical techniques to interpret data and derive actionable insights.
Data Visualization: Create clear, visually compelling dashboards and reports to present findings to stakeholders and senior management.
Experimentation: Design and conduct experiments, including A/B testing, to evaluate hypotheses and measure the effectiveness of different strategies.
Collaboration: Work cross-functionally with product, engineering, and marketing teams to align data insights with business goals.
Algorithm Development: Develop custom algorithms for specific business needs using Python, R, or similar tools.
Educational Background: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or related fields.
Proficiency in programming languages like Python, R, SQL.
Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
Strong understanding of statistics, probability, and advanced mathematical concepts.
Experience with data visualization tools (e.g., Tableau, PowerBI, Matplotlib).
Experience: 2+ years of experience in a data-driven role, working with large datasets and delivering data insights.
Problem-solving Skills: Strong analytical skills and ability to turn complex data into actionable strategies.
Communication Skills: Excellent verbal and written communication to effectively convey technical findings to non-technical stakeholders.
Familiarity with cloud platforms such as AWS, GCP, or Azure.
Experience with big data technologies (e.g., Hadoop, Spark).
Knowledge of Natural Language Processing (NLP) and deep learning techniques.