Data Scientist – AI, ML
1 day ago
Learn how we are redefining the meaning of work, and be a part of the team raved by Clients, Job-seekers and Employees.
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We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.
Requirements
Role Summary
Build AI/ML solutions for People Analytics, Workforce Intelligence, HR Automation, Employee Experience, and Compensation Analytics.
Deliver end-to-end data science projects from discovery to deployment.
Develop predictive models for attrition, performance, and career progression.
Build recruitment analytics and workforce planning models (headcount, skills, succession).
Implement NLP-based sentiment analysis and text analytics.
Develop HR chatbots, resume screening, and document AI pipelines.
Create dashboards, ROI models, and recommendation systems.
Lead POCs in Generative AI, LLMs, and emerging HR tech.
Integrate ML capabilities into products and client solutions.
Present insights to leadership and manage client engagements.
Oversee full project lifecycle from requirements to production.
Bachelor's in Math/Stats/CS/Data Science/Engineering; Master's preferred.
5–6 years of experience in Data Science, ML, AI, model deployment, and solution delivery.
Python (Advanced): OOP, APIs, testing, documentation, production-grade code.
ML & DL: Classical ML, TensorFlow/Keras/PyTorch, time-series, anomaly detection.
NLP: Transformers (BERT/GPT), text classification, sentiment analysis, NER.
ML Engineering: MLOps, model monitoring, retraining, ML pipelines (FastAPI/Flask).
Big Data: Spark/PySpark, large-scale ETL.
Cloud: AWS/Azure/GCP, ML services (SageMaker/AzureML/VertexAI), Docker, Kubernetes.
Generative AI, LLMs, LangChain, RAG, fine-tuning models.
Computer Vision, OCR, Document AI.
Recommendation systems and advanced analytics (A/B testing, causal inference).
Dashboards (Tableau, Power BI, Plotly), SQL, NoSQL, vector DBs.
CI/CD, Git workflows, scalable deployment.
Experience in HR/People Analytics (preferred).
Strong communication and client-facing skills.
Ability to align AI/ML solutions with business goals.
Innovation mindset with POC/prototype experience.
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