Browse Jobs
By Role
By City
Posted Apr 20, 2026
You will be responsible for analyzing large and complex datasets to extract meaningful insights, designing, developing, and deploying machine learning models. Additionally, you will collaborate with cross-functional teams (engineering, product, business), build and optimize data pipelines for structured and unstructured data, and perform data cleaning, feature engineering, and exploratory data analysis (EDA). You will also be expected to present findings using data visualization tools and storytelling techniques, monitor model performance, continuously improve accuracy, and work on real-time and batch data processing systems. - Analyze large and complex datasets
Design, develop, and deploy machine learning models
Collaborate with cross-functional teams
Build and optimize data pipelines
Perform data cleaning, feature engineering, and exploratory data analysis
Present findings using data visualization tools
Monitor model performance and continuously improve accuracy
Work on real-time and batch data processing systems Qualifications required for this role include a Bachelor's degree in Computer Science or a related field along with certification from a recognized institute or university. You should have proven experience of 2 to 3 years as a Data Science Engineer and a minimum of 3 years of experience in Generative AI, Data Analytics, Statistical Modeling, and Process using Python. The required skills for this position include:
Strong proficiency in Python (Pandas, NumPy, Scikit-learn)
Experience with Machine Learning & Statistical Modeling
Hands-on experience with SQL and databases
Knowledge of Data Visualization tools (Power BI, Tableau, Matplotlib, Seaborn)
Experience with ML frameworks (TensorFlow / PyTorch)
Understanding of data pipelines & ETL processes
Familiarity with cloud platforms (AWS / Azure / GCP)
Strong problem-solving and analytical skills Preferred skills for this role consist of experience with Deep Learning (CNNs, RNNs, Transformers), hands-on exposure to Generative AI / LLMs (OpenAI, LangChain, etc.), experience with Big Data tools (Spark, Hadoop), and knowledge of MLOps (Docker, CI/CD, Model Deployment). You will be responsible for analyzing large and complex datasets to extract meaningful insights, designing, developing, and deploying machine learning models. Additionally, you will collaborate with cross-functional teams (engineering, product, business), build and optimize data pipelines for structured and unstructured data, and perform data cleaning, feature engineering, and exploratory data analysis (EDA). You will also be expected to present findings using data visualization tools and storytelling techniques, monitor model performance, continuously improve accuracy, and work on real-time and batch data processing systems. - Analyze large and complex datasets
Design, develop, and deploy machine learning models
Collaborate with cross-functional teams
Build and optimize data pipelines
Perform data cleaning, feature engineering, and exploratory data analysis
Present findings using data visualization tools
Monitor model performance and continuously improve accuracy
Work on real-time and batch data processing systems Qualifications required for this role include a Bachelor's degree in Computer Science or a related field along with certification from a recognized institute or university. You should have proven experience of 2 to 3 years as a Data Science Engineer and a minimum of 3 years of experience in Generative AI, Data Analytics, Statistical Modeling, and Process using Python. The required skills for this position include:
Strong proficiency in Python (Pandas, NumPy, Scikit-learn)
Experience with Machine Learning & Statistical Modeling
Hands-on experience with SQL and databases
Knowledge of Data Visualization tools (Power BI, Tableau, Matplotlib, Seaborn)
Experience with ML frameworks (TensorFlow / PyTorch)
Understanding of data pipelines & ETL processes
Familiarity with cloud platforms (AWS / Azure / GCP)
Strong problem-solving and analytical skills Preferred skills for this role consist of experience with Deep Learning (CNNs, RNNs, Transformers), hands-on exposure to Generative AI / LLMs (OpenAI, LangChain, etc.), experience with Big Data tools (Spark, Hadoop), and knowledge of MLOps (Docker, CI/CD, Model Deployment).
Don't want to apply yourself?
Our team writes your resume, applies for you, preps you for interviews, and negotiates your offer.