About the role. As a Senior Data Scientist, you will uncover valuable insights hidden within vast amounts of data to help clients make smarter business decisions. Your expertise in data mining, statistical analysis, and predictive modeling will drive transformation, enabling the delivery of better products and services.

You will play a key role in managing end-to-end analytics projects, guiding teams, and engaging with clients to integrate data-driven solutions into business processes. Key Responsibilities. Understand business challenges, translate them into analytical problems, and deliver actionable insights.

Organize and analyze data, identifying patterns and trends using machine learning techniques. Develop and optimize classifiers, predictive models, and automation solutions. Perform data mining and leverage state-of-the-art methods to extract valuable insights.

Identify and integrate third-party data sources with internal company data as needed. Enhance data collection procedures to improve analytical capabilities. Process, cleanse, and validate data integrity for analysis.

Conduct ad-hoc analyses and effectively present results to stakeholders. Create automated anomaly detection systems, reports, and dashboards for ongoing monitoring. Manage client communications, project delivery, and mentor junior team members.

Contribute to team development by assisting in recruiting and training emerging talent. Translate business challenges into analytical problems and deliver actionable insights Develop and optimize predictive models, classifiers, and automation solutions using ML techniques Design and build AI solutions chatbots, RAG pipelines, workflow agents,



and multi-agent systems Build Python-based APIs and microservices integrating LLMs (OpenAI, Anthropic, AWS, Azure, GCP) Develop retrieval, embedding, and inference pipelines optimized for performance and scalability Deploy and manage AI workloads across AWS, Azure, and GCP using IaC (Terraform, CloudFormation) Integrate monitoring/logging for model performance; follow AI governance and responsible AI practices Process, cleanse, and validate data; create automated anomaly detection systems and dashboards Manage client communications, mentor junior members, and contribute to recruiting efforts Participate in code reviews and architecture discussions; adhere to clean code practices

Required Skills. Strong problem-solving abilities and excellent communication skills (both oral and written).

Experience in managing analytics projects from conception to deployment. Expertise in machine learning algorithms, including regression, classification, optimization, and neural networks. Solid knowledge of statistical techniques, such as distributions, hypothesis testing, and experimental design.

Proficiency in at least one data science toolkit. Hands-on experience with statistical/analytical tools such as Python or R. Familiarity with databases and query languages,



including RDBMS (Oracle, MS SQL, etc.) and NoSQL/Big Data technologies (MongoDB, Cassandra, Hadoop, HBase).

Competence in data visualization tools such as Tableau, Power BI, QlikView, or D3.js. Proficiency in MS Office tools (Excel, PowerPoint, Word). Strong analytical skills with an ability to collect, organize, and interpret complex data, identifying patterns for business insights.

Programming & AI: Python, GenAI, LLMs, RAG, LangGraph, Autogen, LangChain Data Systems: Vector Databases, Knowledge Graphs, Retrieval Pipelines Cloud AI/ML: AWS (Bedrock, SageMaker), Azure (OpenAI, AI Studio), GCP (Vertex AI, Gemini) MLOps/LLMOps: Deployment, retraining, and evaluation pipelines DevOps: CI/CD, Docker, Kubernetes, event-driven systems ML Expertise: Regression, classification, optimization, neural networks, statistical techniques Databases: RDBMS (Oracle, MS SQL) and NoSQL/Big Data (MongoDB, Cassandra, Hadoop) Visualization: Tableau, Power BI, QlikView, or D3.js Strong problem-solving, communication, and end-to-end project management skills

Preferred Qualifications. 5+ years of hands-on experience in analytics, data science, or machine learning. Bachelor's degree in Engineering, Computer Science, or any field that emphasizes analytical thinking. Masters degree in a relevant field is a plus.

Core Competencies. Analytical, problem-solving, and automation-first mindset. Ability to implement technical solutions that deliver business value. Robust collaboration, communication, and learning skills. Interest in emerging GenAI, AI safety, and automation technologies

📌 Data Scientist/ Senior Data Scientist (Bengaluru)
🏢 Aciesind
📍 Bengaluru