Senior Data Scientist - AI/ML

ACROSSTEK™; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

ACROSSTEK™ is seeking a Senior Data Scientist with a strong foundation in ML, algorithms, statistical modeling, and AI-native development to contribute to advanced AI initiatives and real-time analytics platforms.

This is a hands-on, technically deep role for professionals passionate about building scalable and intelligent ML solutions in Bengaluru. You will design, build, and productionize models, work with real-time data, and collaborate with cross-functional teams.

Qualifications

• 5+ years of experience in Data Science / Applied Machine Learning.
• Advanced proficiency in Python; Scala or similar languages is a plus.
• Strong knowledge of Machine Learning & Statistical Modeling, Clustering & Dimensionality Reduction.
• Strong knowledge of CNNs, RNNs/LSTMs, Transformers & Attention.
• Strong knowledge of Optimization, Bayesian & Probabilistic Modeling.
• Experience taking models from PoC to production.

Responsibilities

• Design, build, and optimize ML models for large-scale datasets.
• Develop solutions for predictive modeling, anomaly detection, forecasting, and automated alerting.
• Apply ML techniques including regression, classification, clustering, and ensemble methods.
• Work with DL architectures such as CNNs, RNNs/LSTMs, Transformers, and attention mechanisms.
• Analyze time-series and complex real-time data.
• Develop POCs and take ML solutions from experimentation to production.
• Process and analyze large-scale datasets using Ray and Spark.
• Collaborate with engineering and product teams to integrate ML models into production.
• Contribute to AI roadmaps and AI-driven product initiatives.
• Leverage AI coding tools such as Claude, Cursor, or GitHub Copilot for development, debugging, prototyping, and solution design.

Skills

Python

Scala

Machine Learning

Statistical Modeling

Clustering

Dimensionality Reduction

CNNs

RNNs/LSTMs

Transformers

Attention

Time-series

Ray

Spark

MLOps

Cloud deployment

LLMs

Tools

Claude

Cursor

GitHub Copilot

Job description

We are looking for a Senior Data Scientist with a strong foundation in Machine Learning, Algorithms, Statistical Modeling, and AI-native development to contribute to advanced AI initiatives and real-time analytics platforms.

This is a hands‑on, technically deep role for professionals passionate about building scalable and intelligent ML solutions.

Key Responsibilities

• Design, build, and optimize ML models for real-world, large-scale datasets.
• Develop solutions for predictive modeling, anomaly detection, forecasting, and automated alerting.
• Apply classical ML techniques including regression, classification, clustering, and ensemble methods.
• Work with deep learning architectures such as CNNs, RNNs/LSTMs, Transformers, and attention mechanisms.
• Analyze time-series and complex real-time data.
• Develop POCs and take ML solutions from experimentation to production.
• Process and analyze large-scale datasets using Ray and Spark.
• Collaborate with engineering and product teams to integrate ML models into production systems.
• Contribute to AI roadmaps and AI-driven product initiatives.
• Leverage AI coding tools such as Claude, Cursor, or GitHub Copilot for development, debugging, prototyping, and solution design.

Required Skills

• 5+ years of experience in Data Science / Applied Machine Learning.
• Advanced proficiency in Python; Scala or similar languages is a plus.
• Strong knowledge of:
  • Machine Learning & Statistical Modeling
  • Clustering & Dimensionality Reduction
  • CNNs, RNNs/LSTMs, Transformers & Attention
  • Optimization, Bayesian & Probabilistic Modeling
• Strong ability to take models from POC to scalable production solutions.
• Hands‑on experience with AI-assisted development tools.
• Strong analytical, problem-solving, and communication skills.

Good to Have

• Experience with real‑time data processing and streaming analytics.
• Strong knowledge of time-series analysis, forecasting, seasonality, and change‑point detection.
• Experience building AI‑powered alerting or anomaly detection systems.
• Knowledge of MLOps and cloud‑based ML deployment.
• Experience with model monitoring, versioning, retraining pipelines, or production ML systems.
• Experience integrating or fine‑tuning LLMs/foundation models.