Senior Data Scientist / AI & Analytics Specialist

Location: India (Hybrid / Onsite as per project)

Experience Required: 6 – 8 Years

Budget: Up to ₹20 LPA

Notice Period: Immediate Joiners Preferred (Replacement Hiring)

About the Role

We are looking for an experienced and highly analytical Senior Data Scientist / AI & Analytics Specialist to join our data-driven innovation team. The ideal candidate will bring a strong foundation in data analysis, machine learning, and practical AI/LLM (Large Language Model) implementations, with hands-on experience transforming data into actionable business insights.

This role demands a mix of technical expertise, business acumen, and applied AI understanding, working closely with cross-functional teams to design intelligent, scalable, and impactful data solutions.

Roles & Responsibilities

• Data Analytics & Engineering:
  Utilise strong SQL and Python skills to extract, transform, and analyse large datasets, uncovering patterns, trends, and business insights.

• Statistical Analysis:
  Apply advanced statistical methodologies to interpret data, perform hypothesis testing, and generate actionable recommendations.

• Machine Learning & AI Implementation:
  Develop and deploy ML models (regression, classification, clustering, time series, etc.) and integrate LLM-based solutions for real-world business use cases such as automation, customer insights, and anomaly detection.

• AI/LLM Application Development:
  Work on prompt engineering, fine-tuning, and model integration using open-source and cloud-based AI frameworks (e.g., LangChain, Hugging Face, Vertex AI).

• Visualisation & Business Insights:
  Design intuitive dashboards and reports using  QlikSense, Power BI, Tableau, or Looker, translating analytical findings into strategic insights.

• Data Storytelling:
  Present findings to both technical and non-technical audiences through compelling visual narratives and executive summaries.

• Advanced Analytics:
  Employ techniques such as predictive modelling, regression analysis, clustering, NLP, and data mining to enhance decision-making.

• Collaboration:
  Work cross-functionally with business, product, and technology teams to understand requirements and convert them into data-driven solutions.

• Cloud & Big Data Integration:
  Leverage GCP BigQuery, Hadoop, or Spark for processing and analysing large-scale datasets. Experience with APIs and DevOps practices is a plus.

Key Skills & Requirements

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or a related quantitative field.

• 6–8 years of experience in data analytics, machine learning, or applied AI.

• Proficiency in SQL and Python (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow).

• Strong foundation in statistical modelling, predictive analytics, and hypothesis testing.

• Experience with LLM concepts, prompt engineering, and generative AI tools (e.g., OpenAI, Anthropic, Ollama, Vertex AI).

• Strong data visualisation skills using Power BI, Tableau, QlikSense, or Looker.

• Familiarity with cloud ecosystems (preferably GCP) and modern data architectures.

• Exposure to Big Data tools such as Hadoop, Spark, or BigQuery.

• Excellent analytical thinking, problem-solving, and communication skills.

• Proven ability to work both independently and collaboratively in fast-paced environments.

Preferred Certifications (Good to Have)

• Google Cloud Certified – Professional Data Engineer / AI Engineer

• Microsoft Certified: Data Scientist Associate

• TensorFlow Developer Certificate

• Generative AI or LLM-related certifications

Desired Attributes

• Strong analytical curiosity and creative problem-solving mindset.

• Ability to translate business problems into technical AI/ML solutions.

• Hands-on approach with a focus on real-world model deployment and performance tuning.

• Detail-oriented, proactive, and collaborative team player.

• Passionate about emerging technologies and continuous learning in AI and Data Science.