Skills and Qualifications:
1. Educational Background:
Bachelors or Masters degree in Data Science, Computer Science, Mathematics, Statistics, or a related field. PhD is a plus.
2. Technical Skills:
a. Strong proficiency in programming languages such as Python, R, or Java.
b. Solid knowledge of statistical analysis and machine learning techniques.
c. Hands-on experience with data manipulation and analysis using libraries like Pandas, NumPy, Scikit-learn, etc.
d. Familiarity with big data technologies such as Hadoop, Spark, or similar.
e. Experience with databases (SQL, NoSQL) and data extraction techniques.
f. Familiarity with cloud platforms such as AWS, GCP, or Azure is a plus.
3. Experience:
a. Proven experience (2-5 years) in a data scientist role or similar.
b. Experience in implementing machine learning models in a production environment is preferred.
c. Experience with deep learning frameworks like TensorFlow, Keras, or PyTorch.
d. Knowledge of NLP (Natural Language Processing) and computer vision techniques.
e. Experience working with large-scale datasets in a cloud computing environment.