Conduct exploratory data analysis to identify patterns, trends, and anomalies within large datasets.
Develop predictive models and machine learning algorithms to solve business problems and improve decision-making processes.
Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
Clean, preprocess, and manipulate data to ensure accuracy, completeness, and consistency.
Implement and deploy scalable solutions for data processing, model training, and evaluation.
Interpret model results and communicate findings to stakeholders in a clear and concise manner.
Stay updated on the latest advancements in data science, machine learning, and related fields.
Mentor junior team members and provide guidance on best practices in data analysis and model development.
Requirements
Master's degree or PhD in Data Science, Machine Learning, AI, Computer Science, Statistics, Mathematics, or a related field. PhD preferred
Proven experience (3+ years post graduate) as a Sr. or Lead Data Scientist in a fast-paced, commercial environment
Have developed algorithms or implemented solutions that include classification, predictive analytics, product recommendation, pattern recognition, sentiment analysis. (E-commerce experience preferred)
Proficiency in machine learning (supervised, semi-supervised & unsupervised)
Proficiency in Python, specifically using its data manipulation libraries
Knowledge and experience with NLP (Natural Language Processing) algorithms and libraries within Python and related languages such as R or Scala.
Strong knowledge of statistical analysis techniques, machine learning algorithms, and data visualization tools
Experience with big data technologies such as Spark and TensorFlow is a plus
Excellent problem-solving skills and ability to work independently as well as part of a team
Strong communication and interpersonal skills, with the ability to explain complex concepts to non-technical stakeholders
Experience working on teams, across functions and able to present to both technical and non-technical audiences and stakeholders
Demonstrated ability to manage multiple projects simultaneously and prioritize tasks effectively
