Senior Data Scientist

4 days ago

Bengaluru, India Aidetic Full time
About the role
As a Senior Data Scientist, you will focus on developing and implementing advanced data science and machine learning models to support our clients’ business needs. This role emphasizes hands-on technical work and collaboration with other data scientists and engineers, under the guidance of the Lead Data Scientist. You will play a key role in creating AI/ML solutions while contributing to our collective knowledge and innovation efforts.
Please apply for the role here - talent.aidetic.ai//user/application-form
About the company
Aidetic is an AI/ML consulting company working at the cutting edge of AI since 2018, before it was cool. We’re a small but highly talented team of 50 people passionate about solving real world problems with AI. With clients such as Target, Tata Steel, InsuranceDekho etc. we have put 200+ AI systems in production.
Expected Compensation
15 to 20 Lakhs Annually
Experience
3-4 years of data science experience
Key Responsibilities
● Data Science & Model Development: Design and implement machine learning and deep learning models, utilizing both supervised and unsupervised techniques to address complex business challenges.
● Data Preparation & Feature Engineering: Conduct data exploration, preprocessing, and feature engineering to create high-quality datasets and features that enhance model effectiveness.
● Advanced Optimization & Evaluation: Apply advanced techniques for hyper-parameter tuning and assess model performance using appropriate evaluation metrics, ensuring model robustness.
● GenAI: Work with developing LLM powered solutions using OpenAI, Claude, or open source LLMs like Llama. Use frameworks like Langchain, Llama Index etc. to develop RAG powered chatbots. Use frameworks such as Crew AI, Autogen etc. to develop agentic workflows.
● MLOps & Deployment: Contribute to the deployment of models with MLOps practices, including versioning, pipeline orchestration, and containerization, ensuring scalability and efficiency.
● API Development & Integration: Use RESTful API frameworks to develop, integrate, and scale data-driven applications within client environments.
● Continuous Learning & Improvement: Stay current with new data science techniques and industry trends, sharing knowledge with the team and contributing to a culture of innovation.
Qualifications
Essential
● Qualification: Bachelor's or Master's degree in a relevant field (Computer Science, Data
Science, Statistics etc.).
● Experience: 3+ years of experience in data science and machine learning.
● Programming & Tools: Proficient in Python, Git, and coding IDEs like VS Code or PyCharm.
● Machine Learning & Deep Learning: Strong knowledge of traditional machine learning algorithms, deep learning, and advanced hyper-parameter tuning.
● Data Manipulation & Analysis: Expertise in data exploration, preprocessing, statistical analysis, feature engineering, and model evaluation.
● MLOps & Deployment: Experience with MLOps basics, containerization tools (Docker, Kubernetes), and cloud platforms (AWS, Azure, Google Cloud).
● GenAI, RAG and AI Agent Frameworks: Proficiency with NLP techniques and familiarity with RAG frameworks like LangChain, LlamaIndex, or CrewAI, Autogen.
● Databases: Familiarity with SQL and NoSQL databases.
● Data Visualization: Ability to create effective data visualizations and basic analytics dashboards.
● Soft Skills: Strong analytical thinking, self-motivation, effective communication, and a high degree of ownership over projects.
Good to Know
● LLM Finetuning and Quantization
● Edge Deployment
● Big Data Technologies: Experience with PySpark, Hadoop, etc.
● Graph Databases: Knowledge of Neo4j, RDF, or similar technologies.
● Messaging Queues: Familiarity with messaging queue systems.

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