Description
You will lead data science initiatives and manage complex statistical modeling projects.
Responsibilities
- Lead the development and implementation of machine learning, statistics, and optimization models.
- Apply NLP and Deep Learning techniques including CNN and RNN to solve complex problems.
- Build and deploy regression, classification, and unsupervised models such as K-Means, DBSCAN, and LOF.
- Work within cross-functional teams to process large data sets using distributed computing tools.
- Own the end-to-end lifecycle of statistical modeling from simulation to production.
Required Skills
- 8-12 years of experience in a statistical or data science role.
- Deep knowledge of machine learning, statistics, and optimization.
- Expertise in Linear and non-Linear Regression, including Multiple and Multivariate models.
- Experience with Classification models and Ensemble techniques.
- Proficiency in NLP and Deep Learning (CNN, RNN).
- Mandatory real-time experience with Python, R, or Matlab.
- Hands-on experience with distributed computing tools like Map/Reduce, Hadoop, Hive, or Spark.
- Degree in Computer Science, Data Science, Mathematics, or a related field.
Preferred Skills
- Experience with semi-structured or unstructured databases such as MongoDB, Cassandra, ArangoDB, Couchbase, or GraphDB.
- Programming proficiency in C, C++, Java, or .Net.