Data Scientist – Machine Learning & Forecasting - Immediate Joiner - Upto 20L
Chennai, Tamil Nadu / Remote (Global), Global
On-site
5-7 Yrs
INR 18-20 LPA
Permanent
4 positions
Job Description
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): Remote (Global), Chennai
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.
Screening Questions
Please note that you will be asked to answer these questions during the application process:
- 1.Total years of experience as Data Scientist
- 2.Current location
- 3.Current CTC (Lakhs per annum)
- 4.Expected CTC (Lakhs per annum)
- 5.Notice period (mention no. of days left to serve if already resigned)
- 6.Are you currently serving notice period?
- 7.Have you built and deployed end-to-end Machine Learning models into production?
- 8.Which forecasting models have you used in the projects?
- 9.Which Machine Learning algorithms have you implemented in production?
- 10.Have you built and deployed end-to-end Machine Learning models into production?
- 11.Have you built data pipelines or worked with MLOps tools?
- 12.What is your primary programming language?
Skills & Technologies
Apply for this Role
Submit your details to apply for this role.