Description

Role Overview :

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.

Responsibilities

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 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.

(ref:hirist.tech)

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