Description

You will build and optimize machine learning models to drive analytical capabilities and data integrity.

This role is on-site.

Responsibilities

• Build and optimize classifiers using machine learning techniques and feature selection.
• Perform data mining, cleansing, and verification to ensure data integrity for analysis.
• Develop automated anomaly detection systems and monitor their performance.
• Integrate third-party data sources and enhance collection procedures for analytic systems.
• Conduct ad-hoc analysis and present findings clearly to stakeholders.

Required Skills

• 5+ years of experience in data science roles.
• Hands-on coding proficiency in Python or R.
• Strong knowledge of statistical modeling, distributions, regression, and statistical testing.
• Expertise in machine learning algorithms including k-NN, Naive Bayes, SVM, and Decision Forests.
• Experience with structured data analysis, unstructured content mining, and NLP.
• Proficiency in SQL, Hive, or Pig.
• Experience with NoSQL databases such as MongoDB, Cassandra, or HBase.
• Familiarity with data science toolkits like NumPy, Pandas, SciKit-Learn, Seaborn, or MatLab.
• Experience with MLOps for model development, release, and monitoring.

Preferred Skills

• Deep learning experience using RNN, LSTM, or CNN with TensorFlow or Keras.
• Data visualization skills using D3.js or GGplot.

Key Skills

Education

Any gradudate