Data Scientist (Machine Learning & Time Series Forecasting) - Remote/Hybrid - upto 20 LPA

Hiring for: A US-based, AI-first data solutions company founded by seasoned technology leaders.
Role: Data Scientist
Positions: 4
Experience: 5 to 7 years
Location(s): Chennai (Hybrid), Bangalore/Hyderabad/Mumbai (Remote)
Type: On-site / Permanent
Salary: Up to INR 20 LPA
Notice Period: Immediate to 30 days
About the Role
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions.
The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact.
Key Responsibilities
Design, develop, and deploy Machine Learning models for business-critical use cases.
Build and optimize traditional ML models such as:
Linear Regression
Logistic Regression
Decision Trees
Random Forest
Gradient Boosting (XGBoost, LightGBM, CatBoost)
Support Vector Machines
Clustering Algorithms
Develop forecasting solutions using:
ARIMA / SARIMA
Prophet
Exponential Smoothing
Time-Series Regression Models
Perform exploratory data analysis (EDA), feature engineering, and data validation.
Evaluate model performance using appropriate statistical and business metrics.
Work with structured and semi-structured datasets from multiple sources.
Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
Build scalable data pipelines and support model deployment in production environments.
Monitor model performance, identify data drift, and implement model retraining strategies.
Present insights and recommendations to technical and non-technical stakeholders.
Required Skills & Qualifications
Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.
Technical Skills
Machine Learning
Strong understanding of supervised and unsupervised learning algorithms.
Experience with ensemble methods and advanced ML techniques.
Expertise in model selection, hyperparameter tuning, and performance optimization.
Forecasting & Statistics
Strong understanding of:
Time-Series Analysis
Forecasting Techniques
Statistical Inference
Hypothesis Testing
Probability Distributions
A/B Testing
Programming
Advanced proficiency in Python.
Experience with:
Pandas
NumPy
Scikit-learn
Statsmodels
XGBoost / LightGBM
Prophet
Data & SQL
Strong SQL skills with experience in complex queries and performance optimization.
Experience working with large-scale datasets.
Visualization
Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.
Cloud & MLOps (Preferred)
Exposure to AWS, Azure, or GCP.
Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices.
Key Competencies
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management abilities.
Ability to work independently in a fast-paced environment.
Strong business acumen and data-driven decision-making mindset.

Work arrangement
No