Description
Make sure to apply with all the requested information, as laid out in the job overview below.
As Data Scientist II, you will support Syneos business goals by helping build and scale innovative data science solutions and products, employing AI, advanced analytics, and machine learning techniques.
RESPONSIBILITIES
- Prototype Machine Learning models and conduct statistical analytics to address complex business challenges with moderate level of guidance and direction.
- Design and implement feature engineering of large datasets and effective exploratory data analysis methodologies.
- Identify meaningful insights, trends, and opportunities from large data and metadata sources and communicate methodologies, caveats, and findings to both technical and non-technical audiences.
- Apply ML techniques and show initiative to learn and adapt to new modeling techniques and procedures.
- Collaborate with technical peers in problem solving and demonstrate iterative thinking and ability to identify next steps based on findings.
QUALIFICATION REQUIREMENTS
Strong programming skills (e.g., Python) and experience with data manipulation and visualization libraries (e.g., Pandas, matplotlib, seaborn) and machine learning frameworks (e.
g. scikit-learn, PyCaret).
- Experience in Traditional ML skills and experience (predictive modeling, recommender systems, insight generation).
- Experience with both supervised and unsupervised machine learning algorithms, statistical analysis, and data manipulation techniques.
- Experience in Causal Inference methodologies.
- Detailed understanding of how data science models are developed and deployed.
- Independent problem-solving and grit. Willingness to own one’s work, and confidence to push best practices. Strong attention to detail.
- Relevant work experience in healthcare or campaign measurement, marketing analytics, and resource optimization in the pharma domain is a plus.
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