Consultant - Data Science (Pharma Commercial)

Chryselys; Hyderabad; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

Chryselys in Hyderabad is seeking a Data Scientist Consultant with 4–6 years of experience in pharmaceutical or healthcare data to transform complex datasets into actionable insights that drive strategic decisions for clients. You will design machine learning models, build scalable data pipelines on Data Lake, and leverage cloud platforms like AWS SageMaker to deliver innovative solutions.

You will create data visualizations and dashboards using PowerBI, Tableau, Qlik, QuickSight, or ThoughtSpot

Qualifications

• Bachelor's or Master's degree in data science, statistics, CS, engineering, or related quantitative field.
• 4–6 years of data science experience in pharma/healthcare.
• Proficient in Python/R with ML libraries (TensorFlow, Scikit-learn, Pandas).
• Strong SQL and cloud data processing (AWS Redshift/Athena/S3); experience with Jupyter Notebooks/SageMaker.

Responsibilities

• Design, develop, and implement ML models and algorithms on pharmaceutical datasets.
• Use advanced statistical methods to derive insights from complex data sources.
• Build data pipelines and scalable ML models on Data Lake using cloud platforms like AWS.
• Collaborate with cross-functional teams to translate business problems into data science solutions.
• Create and present data visualizations and dashboards using PowerBI/Tableau/Qlik/QuickSight to clients.
• Conduct EDA, data profiling, and feature engineering for predictive modeling.
• Evaluate model performance and optimize algorithms for robustness and accuracy.
• Stay updated with ML/AI advances and apply them to projects.

Skills

Python

R

TensorFlow

Scikit-learn

Pandas

SQL

AWS

SageMaker

Jupyter

Education

Bachelor's or Master's in data science/CS/engineering

Tools

AWS Redshift

Athena

S3

SageMaker

PowerBI

Tableau

Qlik

Job description

Role Overview:

As a Data Scientist Consultant at Chryselys, you will leverage advanced analytics, machine learning, and AI to transform complex datasets into actionable insights that drive strategic decision-making for our clients in the pharmaceutical and healthcare industries. You will work closely with cross-functional teams, including client stakeholders, business consultants, and analytics experts, to develop predictive models, optimize operations, and deliver innovative solutions that address critical business challenges.

Key Responsibilities:

• Design, develop, and implement machine learning models and algorithms to analyze pharmaceutical datasets in global markets and provide actionable insights.
• Utilize advanced statistical techniques and data science methodologies to drive insights from complex data sources.
• Build and maintain data pipelines and scalable machine learning models on Data Lake architecture, leveraging cloud-based platforms such as AWS (Redshift, S3, SageMaker, etc.).
• Collaborate with cross-functional teams to translate business problems into data science solutions.
• Create and present data visualizations, dashboards, and reports using tools like PowerBI, Tableau, Qlik, QuickSight, and ThoughtSpot to communicate findings and recommendations to clients.
• Conduct exploratory data analysis, data profiling, and feature engineering to prepare datasets for predictive modelling.
• Evaluate model performance, optimize algorithms, and ensure robustness and accuracy in predictions.
• Stay current with the latest advancements in data science, machine learning, and AI, and apply them to ongoing projects.

What You Bring:

• Education: Bachelor's or master's degree in data science, statistics, computer science, engineering, or a related quantitative field with a strong academic record.
• Experience: 4-6 years of experience in data science, particularly in the pharmaceutical or healthcare industry, working with key datasets like Sales, Claims, and Payer data.
• Skills:
  • Proficiency in programming languages such as Python and R, with a deep understanding of libraries like TensorFlow, Scikit-learn, and Pandas.
  • Strong experience with SQL and cloud-based data processing environments such as AWS (Redshift, Athena, S3), and experience with Jupyter Notebooks/SageMaker.
  • Demonstrated ability to build data visualizations and communicate insights through tools like PowerBI, Tableau, Qlik, QuickSight, or similar.
  • Strong analytical skills, with experience in hypothesis testing, A/B testing, and statistical analysis.
  • Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment.
  • Excellent communication and presentation skills, with the ability to explain complex data science concepts to non-technical stakeholders.
  • A strong problem-solving mindset, with the ability to adapt and innovate in a dynamic consulting environment.