Pharma Data Scientist MLOPS
3 weeks ago
We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations be future ready. We offer accelerated, global growth opportunities for talent that’s bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship, and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com
What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it?
We understand that you are looking for growth in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We believe in creating leaders of tomorrow and mentor our leads to help them grow and nurture them as people managers and account managers.
We are a rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while you work with a team that is fueled by purpose. The combination of this will lead to a truly differentiated experience for you.
If this excites you, then apply below.
Data Scientist, ML Ops
Your impact:
We are seeking a highly skilled Data Scientist with expertise in various modelling algorithms and MLOps to join our dynamic team. The ideal candidate will have a strong background in data science, machine learning, and operationalizing ML models and exposure to pharma commercial analytics. You will work closely with cross-functional teams to develop, deploy, and maintain machine learning models that drive business insights and innovation.
Key Responsibilities:
- We are looking for experienced data science professional, who can handle commercial analytics projects with proficiency. Additionally, domains expertise on Sales Force analytics or Payer analytics or Patient or digital analytics or Brand Performance analytics will be a value add
- Model Development: Design, develop, and implement machine learning models through EDA, feature engineering and using a variety of algorithms (e.g., regression, classification, clustering, neural networks, ensemble methods)
- MLOps: Establish and maintain MLOps practices to ensure seamless deployment, monitoring, and maintenance of ML models in production environments.
- Model Evaluation: Evaluate model performance using appropriate metrics and techniques, and iterate on models to improve accuracy and efficiency.
- Collaboration: Work closely with data engineers and business stakeholders to integrate ML models into applications and workflows.
- Documentation: Document model development processes, assumptions, and results to ensure reproducibility and transparency.
- Continuous Learning: Stay updated with the latest advancements in AI/ML including LLMs, MLOps, to continuously improve skills and knowledge.
About you:
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- Experience: 4+ years of experience in data science and machine learning, with a focus on model development and MLOps.
- Domain Expertise: Experience in pharma commercial analytics for at least 2+ years preferably in sales force targeting, patient journey predictions
- Technical Skills: Proficiency in programming languages such as Pyspark, Python or R, and experience with ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- MLOps Tools: Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model deployment and monitoring.
- Data Handling: Strong skills in SQL and experience in snowflake, Dataiku, Databricks is a plus
- Problem-Solving: Excellent analytical and problem-solving skills, with the ability to translate business problems into data science solutions.
- Communication: Strong communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.
EQUAL OPPORTUNITY
Indegene is proud to be an Equal Employment Employer and is committed to the culture of Inclusion and Diversity. We do not discriminate on the basis of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical ability, or any other characteristics. All employment decisions, from hiring to separation, will be based on business requirements, candidate’s merit and qualification. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristics.
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