Senior Associate Data Science (Pharma Domain)

Were Hiring: Senior Associate – Insights & Analytics at Chryselys

Location:

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About Us:

Chryselys

We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights.

Who we are:

People -

Quality -

Technology

Role Overview:

As a Data Scientist Senior Associate 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 (e.g., IQVIA, Symphony, Veeva, Open data) 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:

Experience:

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.