Senior Data Scientist

InfraCents Pvt. Ltd.; India; Remote; INR 1,800,000 - 3,200,000; Full time

Job summary

InfraCents Pvt. Ltd. is seeking a Senior Data Scientist to lead data science engagements, framing problems, developing models, and delivering to production. You will set analytical standards and ensure models deliver measurable business value by working directly with client leadership.

The role blends deep statistics and ML with stakeholder management, requiring collaboration with ML engineers for serving, monitoring, and drift detection. Leadership experience is valued.

Qualifications

• 4-7 years of data science or applied ML experience.
• Production models with measurable business impact.
• Strong statistics, ML and experimentation skills; aware of failure modes.
• Production mindset with collaboration with engineering for deployment.
• Leadership experience guiding projects and mentoring juniors.

Responsibilities

• Lead data science engagements from problem framing to production delivery.
• Define success metrics and communicate impact to stakeholders.
• Mentor data scientists and contribute to hiring and technical content.

Skills

Statistics

Machine Learning

Experimentation

Production deployment

Leadership

Client communication

Education

Bachelor's or Master's in CS/Statistics/Math/Economics

PhD welcome but not required

Tools

Python

SQL

R

scikit-learn

XGBoost

LightGBM

PyTorch

Statistical packages

Job description

About InfraCents

InfraCents is a software engineering company. We design and build software products, run the cloud platforms they live on, build AI systems and data pipelines, and keep all of it secure, reliable and cost-efficient in production. Our engineers work directly with clients, own outcomes end to end and are trusted with real production systems. We value clear thinking, honest communication and work that still holds up a year after it ships.

Role Overview

The Senior Data Scientist will lead data science engagements for clients, owning problem framing, methodology, model development and the path to production. You will set analytical standards, review the work of others and make sure models deliver measurable business value.

The role combines deep statistical and ML expertise with stakeholder management: you will work directly with client leadership to prioritise use cases and measure outcomes.

Key Responsibilities: Technical Leadership

• Lead the design of modelling approaches for forecasting, pricing, risk, recommendation and optimisation problems.
• Set standards for validation, experimentation and reproducibility.
• Review models and analyses for statistical rigour and business relevance.

Key Responsibilities: Delivery & Production

• Own data science projects from discovery to deployed, monitored models.
• Work with ML engineers on model serving, feature pipelines and drift monitoring.
• Define success metrics and report impact to stakeholders.

Key Responsibilities: People & Client Engagement

• Mentor data scientists and contribute to hiring.
• Run discovery sessions with clients to identify high-value data and AI use cases.
• Support proposals and contribute to case studies and technical content.

Who We're Looking For

• Experience: 4-7 years in data science, with models running in production and measurable business impact.
• Depth: Expert in statistics, ML and experimentation, including their failure modes.
• Production mindset: Has worked closely with engineering to deploy and maintain models.
• Leadership: Has led projects and mentored other data scientists.
• Client exposure: Confident presenting to senior stakeholders and handling challenging questions.

Technical Expertise Required

• Languages: Python, SQL, R (optional)
• ML & Statistics: scikit-learn, XGBoost / LightGBM / CatBoost, PyTorch, statsmodels, Causal inference (DoWhy / EconML)
• Forecasting: statsforecast / Prophet, Darts, Hierarchical forecasting
• Data Platforms: Databricks, Snowflake, BigQuery, Spark, dbt
• MLOps: MLflow, SageMaker / Vertex AI, Feast, Evidently (drift monitoring), Airflow
• Generative AI: LLMs for analytics and text data, Embeddings, Evaluation of LLM outputs

Nice to Have

• Experience with optimisation (linear programming, OR-Tools).
• Experience with recommendation systems or pricing models.
• Publications, Kaggle achievements or conference talks.

Qualifications

• Experience: 4-7 years in data science or applied ML, with 1+ years leading projects.
• Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Economics or a related field. A PhD is welcome but not required.