Senior Data Scientist (Advanced Modeling & Machine Learning)
Posted 15 days ago
Job Viewed
Job Description
Job Title: Senior Data Scientist (Advanced Modeling & Machine Learning)
Location: Remote
Location Preference: We are specifically looking to hire talented individuals from Tier 2 and Tier 3 cities for this opportunity.
Job Type: Full-time
About the role
We are seeking a highly motivated and experienced Senior Data Scientist with a strong background in statistical modeling, machine learning, and natural language processing (NLP). This individual will work on advanced attribution models and predictive algorithms that power strategic decision-making across the business. The ideal candidate will have a Master’s degree in a quantitative field, 4–6 years of hands-on experience, and demonstrated expertise in building models from linear regression to cutting-edge deep learning and large language models (LLMs). A Ph.D. is strongly preferred.
Responsibilities
- Responsible for analyzing the data, identifying patterns, and do a detailed EDA.
- Build and refine predictive models using techniques such as linear/logistic regression, XGBoost, and neural networks.
- Leverage machine learning and NLP methods to analyze large-scale structured and unstructured datasets.
- Apply LLMs and transformers to develop solutions in content understanding, summarization, classification, and retrieval.
- Collaborate with data engineers and product teams to deploy scalable data pipelines and model production systems.
- Interpret model results, generate actionable insights, and present findings to technical and non-technical stakeholders.
- Stay abreast of the latest research and integrate cutting-edge techniques into ongoing projects
Required Qualifications
- Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
- 4–6 years of industry experience in data science or machine learning roles.
- Strong statistical foundation, with practical experience in regression modeling, hypothesis testing, and A/B testing.
- Hands-on knowledge of:
> Programming languages : Python (primary), SQL, R (optional)
> Libraries : pandas, NumPy, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, spaCy, Hugging Face Transformers
> Distributed computing : PySpark, Dask
> Big Data and Cloud Platforms : Databricks, AWS Sagemaker, Google Vertex AI, Azure ML
> Data Engineering Tools : Apache Spark, Delta Lake, Airflow
> ML Workflow & Visualization : MLflow, Weights & Biases, Plotly, Seaborn, Matplotlib
> Version control and collaboration : Git, GitHub, Jupyter, VSCode
Preferred Qualifications
- Masters or Ph.D. in a quantitative or technical field.
- Experience with deploying machine learning pipelines in production using CI/CD tools.
- Familiarity with containerization (Docker) and orchestration (Kubernetes) in ML workloads.
- Understanding of MLOps and model lifecycle management best practices.
- Experience in real-time data processing (Kafka, Flink) and high-throughput ML systems.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and remote options
- Opportunities for continued learning and research
- Collaborative, high-impact team environment
- Access to cutting-edge technology and compute resources
To apply, send your resume to to be part of a team pushing the boundaries of data-driven innovation.
Senior Data Scientist (Advanced Modeling & Machine Learning)
Posted 15 days ago
Job Viewed
Job Description
Job Title: Senior Data Scientist (Advanced Modeling & Machine Learning)
Location: Remote
Location Preference: We are specifically looking to hire talented individuals from Tier 2 and Tier 3 cities for this opportunity.
Job Type: Full-time
About the role
We are seeking a highly motivated and experienced Senior Data Scientist with a strong background in statistical modeling, machine learning, and natural language processing (NLP). This individual will work on advanced attribution models and predictive algorithms that power strategic decision-making across the business. The ideal candidate will have a Master’s degree in a quantitative field, 4–6 years of hands-on experience, and demonstrated expertise in building models from linear regression to cutting-edge deep learning and large language models (LLMs). A Ph.D. is strongly preferred.
Responsibilities
- Responsible for analyzing the data, identifying patterns, and do a detailed EDA.
- Build and refine predictive models using techniques such as linear/logistic regression, XGBoost, and neural networks.
- Leverage machine learning and NLP methods to analyze large-scale structured and unstructured datasets.
- Apply LLMs and transformers to develop solutions in content understanding, summarization, classification, and retrieval.
- Collaborate with data engineers and product teams to deploy scalable data pipelines and model production systems.
- Interpret model results, generate actionable insights, and present findings to technical and non-technical stakeholders.
- Stay abreast of the latest research and integrate cutting-edge techniques into ongoing projects
Required Qualifications
- Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
- 4–6 years of industry experience in data science or machine learning roles.
- Strong statistical foundation, with practical experience in regression modeling, hypothesis testing, and A/B testing.
- Hands-on knowledge of:
> Programming languages : Python (primary), SQL, R (optional)
> Libraries : pandas, NumPy, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, spaCy, Hugging Face Transformers
> Distributed computing : PySpark, Dask
> Big Data and Cloud Platforms : Databricks, AWS Sagemaker, Google Vertex AI, Azure ML
> Data Engineering Tools : Apache Spark, Delta Lake, Airflow
> ML Workflow & Visualization : MLflow, Weights & Biases, Plotly, Seaborn, Matplotlib
> Version control and collaboration : Git, GitHub, Jupyter, VSCode
Preferred Qualifications
- Masters or Ph.D. in a quantitative or technical field.
- Experience with deploying machine learning pipelines in production using CI/CD tools.
- Familiarity with containerization (Docker) and orchestration (Kubernetes) in ML workloads.
- Understanding of MLOps and model lifecycle management best practices.
- Experience in real-time data processing (Kafka, Flink) and high-throughput ML systems.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and remote options
- Opportunities for continued learning and research
- Collaborative, high-impact team environment
- Access to cutting-edge technology and compute resources
To apply, send your resume to to be part of a team pushing the boundaries of data-driven innovation.
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