We are looking for a Senior Data Scientist who can translate business problems into deployable analytics, machine learning, and AI solutions. This is not a purely research-focused role. Our data scientists work closely with consulting teams, data engineers, and client stakeholders to design models and analytical systems that improve real business decisions and operational workflows.

You will be responsible for framing analytical problems, developing predictive and machine learning models, and ensuring that these solutions can be deployed and adopted in production environments.

What You Will Work On :

You will contribute to enterprise data and AI programs such as :

- Designing predictive models that support operational decision making

- Developing fraud detection, risk scoring, and forecasting solutions

- Building recommendation engines and decision-support models

- Creating AI and LLM-enabled copilots for enterprise workflows

- Deploying analytics models that integrate directly into business processes

Your work will move beyond model experimentation - you will help ensure that models deliver measurable business impact.

Key Responsibilities :

Problem Framing & Analytics Design :

- Work with consulting teams and client stakeholders to translate business problems into analytical use cases

- Define metrics, hypotheses, and analytical approaches for solving enterprise problems

- Identify relevant data sources and design analytical frameworks

Model Development & Evaluation :

- Develop predictive models using statistical and machine learning techniques

- Perform exploratory data analysis (EDA) to identify patterns and insights

- Implement feature engineering, model selection, and performance evaluation

Production Deployment & Impact :

- Work with data engineers to productionize models and analytics workflows

- Monitor model performance and ensure reliability over time

- Ensure that model outputs integrate effectively into operational workflows

Collaboration & Delivery :

- Present insights and analytical findings to both technical and business stakeholders

- Collaborate with cross-functional teams including engineers, consultants, and client teams

- Contribute to solution design discussions for enterprise AI programs

Required Experience :

- 6 - 12 years of experience in data science, machine learning, or advanced analytics roles

- Hands-on experience building and deploying predictive models in production environments

- Strong experience working with large datasets and modern analytics platforms

Core Technical Skills :

Programming & Data Analysis :

- Strong proficiency in Python

- Strong SQL capabilities for working with large datasets

- Experience with data manipulation libraries such as Pandas or Polars

Machine Learning :

- Experience with supervised and unsupervised machine learning techniques

- Strong understanding of feature engineering, model selection, and evaluation methods

- Experience using modern ML libraries such as scikit-learn, XGBoost, LightGBM, or CatBoost

Analytics & Statistical Thinking :

- Strong foundation in statistics, hypothesis testing, and experimental design

- Ability to translate business questions into measurable analytical approaches

Data Platforms :

- Experience working with modern data platforms such as Databricks, Snowflake, or BigQuery

- Familiarity with cloud-based ML platforms such as AWS SageMaker, Vertex AI, or Azure ML

Preferred Experience :

- Experience deploying ML models into production environments

- Exposure to MLOps practices (experiment tracking, model monitoring, versioning)

- Experience working with LLMs or generative AI applications

- Familiarity with feature stores, model monitoring tools, or ML pipelines

- Experience working in consulting or client-facing analytics roles

What Makes Someone Successful in This Role :

We look for data scientists who :

- Think in terms of business impact, not just model performance

- Can convert ambiguous business problems into structured analytical solutions

- Are comfortable working in consulting-led transformation programs

- Balance statistical rigor with practical delivery

- Can communicate complex analytical insights clearly to non-technical stakeholders

Why Join Greyamp :

- Work on real production AI and analytics systems for enterprise clients

- Collaborate with consulting teams solving complex transformation problems

- Exposure to global enterprise programs across multiple industries

- Opportunity to shape and grow Greyamps data and AI practice

Final Note :

At Greyamp, data science is not just about building models. It is about designing analytical systems that improve enterprise decisions and enable AI- driven transformation.

If you enjoy solving real-world business problems with data and working in a fast-moving consulting environment, we would love to speak with you.