Data Scientist A

Data Scientist

Experience: 2-3 years | Location: Bengaluru (Hybrid)

Akaike Technologies is a dynamic and innovative AI-driven company dedicated to building impactful solutions. Our mission is to empower businesses by harnessing the power of data and AI to drive growth, efficiency, and value. We foster a culture of collaboration, creativity, and continuous learning.

Experience Pre-Requisite : Having 2 years of experience, all of which relevant into Data Science

Job Description: Focus on Classical Machine Learning (70%) and Generative AI (30%)

We are seeking an experienced and highly skilled Senior Data Scientist to join our team in Bengaluru. This role focuses on driving innovative, large-scale solutions using cutting-edge Classical Machine Learning, PySpark, Spark SQL, and Generative AI. The ideal candidate will possess a blend of deep technical expertise, strong business acumen, effective communication skills, sense of ownership & be motivated towards establishing quantifiable business impact. We require a proven track record in designing, developing, and real-time deploying scalable ML/DL pipelines and LLM Agents in a fast-paced, collaborative environment.

Key Responsibilities

Large-Scale Data Handling, PySpark, & Databricks Deployment

• Efficiently handle and model billions of data points using multi-cluster data processing frameworks (PySpark, Spark SQL).
• Expertise on Databricks/AWS is a must have: Ability to design, write, scale, and monitor end-to-end ML Pipelines on Databricks/AWS.
• Proven expertise to run and manage Databricks data pipelines in real time for low-latency decision-making.
• Develop and implement scalable deployment pipelines using Docker and AWS services (ECR, Lambda, Step Functions).
  
  

• Owning the entire workstreams end to end, from initial designs & POC by building custom machine learning solutions as needed till the business impact calculation of the use-case while ensuring modularity, scalability, and production-ready codebase.
• Design and implement custom models, loss functions and be able to handle nuanced conversations of trade offs between various modelling choices.
• Apply specialized modeling for marketing scenarios (Targeting, Budget optimisation, Churn) and data limitations (Sparse/incomplete labels, Single class learning).
  
  

• Practical experience in building LLM-ready Data Management layers for large-scale structured and unstructured data.
• Apply foundational understanding of LLM Agents and multi-agent systems (e.g., Agent-Critique, ReACT, Agent Collaboration), advanced prompting, LLM evaluation, confidence grading, and Human-in-the-Loop systems.
  
  

• Proficiency in Python and its data science ecosystem (NumPy, Pandas, Dask, PySpark) for large-scale data processing.
• Expert, hands-on experience with Databricks for MLOps, pipeline orchestration, and real-time deployment.
• Ability to perform effective feature engineering by understanding complex business objectives.
  
  

• Classical ML : Tree Based Models, GLMs’, Clustering Models etc.
• Deep Learning : ANN, 1D/2D/3D Convolutional Neural Networks (ConvNets), LSTMs, Transformer models.
• Strong proficiency in PU learning, single-class learning, representation learning, alongside traditional ML approaches.
• Advanced understanding and application of model explainability techniques (e.g., SHAP, LIME).
• Hands-on experience with ML/DL libraries such as Scikit-learn, TensorFlow/Keras, and PyTorch.
  
  

• Experience utilizing large-scale language models (GPT-4, Mistral, Llama, Claude) through prompt engineering and custom fine tuning.
• Code Versioning Systems : Github, Git
  
  

• Communication Skills : Of all the things, this is perhaps the most important soft skill for us, you must be able toCapture the attention of your audience - usually in client calls Succinctly put across your ideas to your team members Bring clarity of thought and next steps to the table and present it well.
• Presentation Skills : Be able to visually present your ideas on a white board Be able to build a compelling presentation for CxOs in a top down manner with an angle of business impact in mind.
• Problem Solving Skills : Be able to leverage various internal tools, client datasets to craft a problem in the shortest time possible. Be able to make trade-offs keeping the timelines in mind.
  
  

• Background in Pharma Domain.
• Knowledge of Recommender Systems & Next Best Action Systems.