Data Scientist (Machine Learning)

Company

hirify.global delivers data science and analytics solutions for the commercial pharma and life sciences sector.

What you will do

• Develop, train, evaluate, and deploy scalable machine learning, statistical, and advanced algorithmic models.
• Build data science solutions using Python, PySpark, and Apache Spark with Scala, Python, or Java.
• Implement NLP capabilities including text classification, named entity recognition, topic modeling, and sentiment analysis.
• Apply deep learning and modern AI methods involving LLMs, LSTMs, GRUs, and transformers.
• Operationalize models in production workbench environments and cloud platforms.
• Plan and track tasks, communicate results, and collaborate with large cross-functional teams.

Requirements

• 5+ years of hands-on experience developing and operationalizing machine learning models.
• Strong proficiency in Python and machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras, SparkML, NumPy, and pandas.
• Experience with Apache Spark or Hadoop and cloud platforms such as AWS, Azure, or GCP.
• Knowledge of statistical and probabilistic methods, including SVM, decision trees, bagging, boosting, and clustering.
• Experience applying machine learning algorithms across classification, regression, deep learning, and NLP.
• BE/B.Tech degree, analytical problem-solving skills, communication ability, ownership, and teamwork.

Nice to have

• Experience with Databricks or Dataiku DSS.
• Familiarity with recommender systems and reinforcement learning.
• Understanding of commercial pharma, patient data, and analytics.
• Experience with Git, Jira, and Confluence.

Culture & Benefits

• Work in a challenging, results-oriented environment.
• Emphasis on self-motivation, continuous learning, ownership, and cultural fit.
• Opportunities to contribute to teamwork, leadership, talent management, capability building, and thought leadership.
• Focus on logical thinking, task management, communication, and business impact.