Senior Data Scientist

• Frameworks: TensorFlow, Keras, PyTorch

• CNNs, RNNs, LSTMs, Transformers

• Use cases: NLP, computer vision, time-series forecasting

4. Data Wrangling & Preprocessing

• Missing data handling

• Feature engineering

• Data cleaning

• Outlier detection

• Normalization/standardization

5. Data Visualization & BI Tools

• Python: Matplotlib, Seaborn, Plotly

• Tools: Tableau, Power BI

• Dashboards, reporting, storytelling with data

6. Big Data & Cloud Tools (Needed for production-scale roles)

• Big Data Frameworks: Spark, Hadoop

• Cloud Platforms (any one strongly):

o AWS (S3, EC2, SageMaker) o Azure (Data Factory, Databricks, ML Studio) o GCP (BigQuery, Vertex AI)

7. Deployment Skills (advanced roles)

• Model deployment: Flask, FastAPI

• Docker, Kubernetes (optional)

• CI/CD basics

8. Databases & Data Engineering Basics

• Relational: MySQL, PostgreSQL, SQL Server

• NoSQL: MongoDB, Cassandra

• Data pipelines: Airflow, Prefect (optional)

Roles & Responsibilities

• Define the ML use case, success metrics, and evaluation criteria; Liaise with business directly and translate business needs into an ML approach.

• Perform data exploration, data quality checks, feature engineering, and dataset preparation for training and testing.

• Build, train, validate, and iterate ML models; compare experiments and select the best candidate model.

• Package the solution f or production (e.g., containerized scoring/service endpoint) and support deployment with engineering/MLOps practices

• Set up basic monitoring (model accuracy/health) and support continuous improvement post release. Required Skills & Experience

1. Programming Languages

• Strong Python familiarity (hands on) for data prep, modeling, and building ML components.

• SQL - Skills: joins, window functions, CTEs, query optimization

2. Machine Learning

• Linear/Logistic Regression

• Decision Trees, Random Forest, XGBoost, LightGBM

• SVM, KNN

• Model evaluation - Precision/Recall, F1, ROC-AUC, MSE, RMSE

• Model tuning - Grid search, randomized search, cross validation, * Solid foundation in ML concepts (supervised/unsupervised, evaluation, validation) and practical experimentation.

• Experience taking models to production in a cloud agnostic way (portable design; API/service mindset).

• Working knowledge of version control and basic CI/CD-style collaboration with engineering teams., Qualifications : BACHELOR OF COMPUTER SCIENCE You must create an Indeed account before continuing to the company website to apply

Salary Range: $125,000-$145,000 a year TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays.