61 Data Mining jobs in Indore

Our client, a global leader in the maritime industry, is seeking a talented Data Science Analyst to join their dynamic team in Mumbai.

Data Science Analyst

based in Andheri, Mumbai, India

ORGANIZATION : This position reports to Senior Data expert in the company headquarters. You will be part of the global analytics function that builds and drives data-driven decision-making across the organization. This role focuses on developing analytics platforms, dashboards, and predictive models that enhance operational efficiency and business intelligence across the company’s global fleet and offices. If you enjoy solving complex data challenges, building analytical solutions, and turning insights into real-world impact, this is an excellent opportunity to be part of an innovative team shaping the future of maritime analytics.

Key Responsibilities:

• Lead and deliver analytics projects from concept to completion, aligned with the company’s analytics roadmap.
• Source, cleanse, and transform raw data from large-scale systems to create strong foundations for modelling and dashboarding.
• Develop, validate, and deploy machine learning models using Python or R, leveraging modern ML libraries such as Scikit-learn or PyTorch.
• Build interactive and user-friendly dashboards using Tableau or Power BI, ensuring data is translated into actionable insights.
• Conduct exploratory data analysis (EDA) to identify trends and opportunities that drive strategic business outcomes.
• Collaborate with IT and operations teams across India and Hong Kong to design scalable, high-quality analytical solutions.
• Communicate findings effectively to senior stakeholders and non-technical users through visual and written reports.
• Promote data governance, best practices, and data literacy across the organization.

Your Profile:

• Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, or a related quantitative field.
• 5+ years of hands-on experience in Data Analytics or Data Science roles.
• Proficiency in SQL and experience working with NoSQL or Graph Databases.
• Demonstrated experience building machine learning models and deploying them in production environments.
• Strong working knowledge of data visualization tools such as Tableau or Power BI.
• Familiarity with Git for version control and collaborative development.
• Excellent analytical, problem-solving, and communication skills with the ability to simplify complex data for decision-makers.
• Experience with Big Data technologies (e.g. Spark, Hive, Presto) or cloud platforms (AWS, Azure, Google Cloud) will be an advantage.
• Exposure to Generative AI tools and frameworks such as LangChain, Vertex AI, or Hugging Face will be a plus.

The Offer:

• Join us to make a significant impact in the maritime industry through cutting-edge data analytics.
• A competitive remuneration package with benefits.
• Work with a global leader in the shipping industry.

RECRUITMENT PROCESS: Please apply with an updated resume. All applications will be treated as strictly confidential. Our team will review your application and a consultant will get in touch with you accordingly.

Comaea Consulting

NLP Data Science Intern

Did you notice a shortage of food at supermarkets during covid? Have you heard about the recent issues in the global shipping industry? or perhaps you’ve heard about the shortages of microchips? These problems are called supply chain disruptions. They have been increasing in frequency and severity. Supply chain disruptions are threatening our very way of life.

Our vision is to advance society’s capacity to withstand shocks and stresses. Kavida.ai believes the only way to ensure security is through supply chain resiliency. We are on a mission to help companies proactively manage disruption supply chain disruption risks using integrated data.

Our Story

In March 2020 over 35 academics, data scientists, students, and software engineering volunteers came together to address the food shortage issues caused by the pandemic - Covid19foodsupply.com. A core team of 9 was formed and spun off into a startup and the rest is history.

Our investors include one of the world's largest supply chain quality & compliance monitoring companies, a £1.25bn apparel manufacturer, and some very impressive angel investors.

Social Impact:

Social impact is in our DNA. We believe private sector innovation is the only way to address social problems at scale. If we achieve our mission, humanity will always have access to its essential goods for sustenance. No more shortages of food, PPE, medicine, etc.

Our Culture :

Idea Meritocracy:

The best ideas win. We only care about what is right, not who is right. We know arriving at the best answer requires constructive tension. Sometimes it can get heated but it's never personal. Everyone contributes to better ideas knowing they will be heard but also challenged.

Drivers Not Passengers:

We think as owners who drive the bus, not as passengers. We are self-starters and never wait for instructions. We are hungry for autonomy, trust, and responsibility. Everyone is a leader because we know leadership is a trait, not a title. Leaders drive growth and navigate the chaos.

We Figure Out The Answers:

We trust our ability to figure stuff out. We do not need all the information to start answering the question. We can connect the dots and answer difficult questions with logic.

Customer & Mission Obsessed:

Our customers are our heroes and we are obsessed with helping them. We are obsessed with; understanding their supply chains better, resolving their biggest headaches, and advancing their competitiveness.

Learning and growth

We all take personal responsibility for becoming smarter, wiser, more skilled, happier. We are obsessed with learning about our industry and improving our own skills. We are obsessed with our personal growth; to become more.

Job Description:

As a member of our Research team, you will be responsible for researching, developing, and coding Agents using state-of-the-art LLM's with automated pipelines.

• Write code for the development of our ML engines and micro-services pipelines.
• use, optimize, train, and evaluate state-of-the-art GPT models.
• research and Develop Agentic pipelines using LLM's.
• research and develop RAG based pipeline using vector DB's .

Essential Requirements:

• prompt engineering and Agentic LLm frameworks like langchain/llama index
• good enough undersanding of vectors/tensors and RAG pipelines
• Knowledge of building NLP systems using transfer learning or building custom NLP systems from scratch using TensorFlow or PyTorch.
• In-depth knowledge of DSA, async, python, and containers.
• Knowledge of transformers and NLP techniques is essential, and deployment experience is a significant advantage.

Salary Range: ₹15000 - ₹25000

We are offering a full-time internship position to final-year students. The internship will last for an initial period of 6-12 months before converting to a full-time job, depending on suitability for both parties. If the applicant is a student who needs to return to university, they can continue with the program on a part-time basis.

• Intensive training in data analysis techniques, statistical modeling, and machine learning algorithms.
• Exposure to programming languages commonly used in data science, such as Python and R.
• Hands-on experience with data manipulation, cleaning, and preparation tools.
• Learn to build and evaluate predictive models and machine learning pipelines.
• Develop skills in data visualization and storytelling to communicate insights effectively.
• Work on challenging projects that address real business problems.
• Receive mentorship from senior data scientists and guidance on career development.
• Collaborate within a remote team environment, enhancing communication and teamwork skills.
• Opportunity to contribute to innovative data-driven solutions.
• Potential for full-time employment upon successful completion of the trainee program.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong academic record and a demonstrated interest in data analysis and machine learning.
• Foundational knowledge of programming concepts, preferably in Python or R.
• Excellent analytical and problem-solving abilities.
• Strong communication and interpersonal skills, crucial for remote collaboration.
• Eagerness to learn and adapt to new tools and methodologies.
• Ability to work independently and manage time effectively in a remote setting.
• A proactive and curious mindset towards data exploration and discovery.

• Assist senior data scientists in data collection, cleaning, and preprocessing tasks.
• Perform exploratory data analysis to identify trends, patterns, and insights.
• Support the development and validation of machine learning models under guidance.
• Create data visualizations to communicate findings effectively to team members.
• Learn and apply various statistical techniques and data mining methods.
• Contribute to documentation of data processes, models, and findings.
• Participate in team meetings and knowledge-sharing sessions.
• Gain exposure to various data science tools and technologies such as Python, R, SQL, and data visualization libraries.
• Collaborate with team members on assigned tasks and projects.
• Actively seek feedback and opportunities for learning and skill development.
• Help in the preparation of reports and presentations summarizing analytical outcomes.

• Bachelor's degree or current enrollment in a Bachelor's or Master's program in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, Physics, or Engineering.
• Strong analytical and quantitative skills with a demonstrable interest in data science.
• Basic understanding of programming concepts, preferably in Python or R.
• Familiarity with database concepts and SQL is a plus.
• Excellent problem-solving abilities and attention to detail.
• Strong communication and interpersonal skills, essential for remote collaboration.
• Eagerness to learn and adapt to new technologies and methodologies.
• Ability to work independently and manage time effectively in a remote setting.
• Prior exposure to data analysis projects (academic or personal) is advantageous.
• A proactive and curious mindset.

**We are currently hiring for a senior-level position and are looking for immediate joiners only.

If you are interested, please send your updated resume to along with details of your CTC, ECTC and notice period **

Location: Remote

Employment Type: Full-time

About the Role

The QA Engineer will own quality assurance across the ML lifecycle—from raw data validation through

feature engineering checks, model training/evaluation verification, batch prediction/optimization

validation, and end-to-end (E2E) workflow testing. The role is hands-on with Python automation, data

profiling, and pipeline test harnesses in Azure ML and Azure DevOps. Success means provably correct

data, models, and outputs at production scale and cadence.

About the Role

The QA Engineer will own quality assurance across the ML lifecycle—from raw data validation through

feature engineering checks, model training/evaluation verification, batch prediction/optimization

validation, and end-to-end (E2E) workflow testing. The role is hands-on with Python automation, data

profiling, and pipeline test harnesses in Azure ML and Azure DevOps. Success means provably correct

data, models, and outputs at production scale and cadence.

Key Responsibilities

● Test Strategy & Governance

○ Define an ML-specific Test Strategy covering data quality KPIs, feature consistency

checks, model acceptance gates (metrics + guardrails), and E2E run acceptance

(timeliness, completeness, integrity).

○ Establish versioned test datasets & golden baselines for repeatable regression of

features, models, and optimizers.

● Data Quality & Transformation

○ Validate raw data extracts and landed datalake data: schema/contract checks,

null/outlier thresholds, time-window completeness, duplicate detection, site/material

coverage.

○ Validate transformed/feature datasets: deterministic feature generation, leakage

detection, drift vs. historical distributions, feature parity across runs (hash or statistical

similarity tests).

○ Implement automated data quality checks (e.g., Great Expectations/pytest +

Pandas/SQL) executed in CI and AML pipelines.

● Model Training & Evaluation

○ Verify training inputs (splits, windowing, target leakage prevention) and

hyperparameter configs per site/cluster.

○ Automate metric verification (e.g., MAPE/MAE/RMSE, uplift vs. last model, stability

tests) with acceptance thresholds and champion/challenger logic.

○ Validate feature importance stability and sensitivity/elasticity sanity checks (pricevolume

monotonicity where applicable).

○ Gate model registration/promotion in AML based on signed test artifacts and

reproducible metrics.

● Predictions, Optimization & Guardrails

○ Validate batch predictions: result shapes, coverage, latency, and failure handling.

© 2025 Insurge Partners. All rights reserved.

○ Test model optimization outputs and enforced guardrails: detect violations and prove

idempotent writes to DB.

○ Verify API push to third party system (idempotency keys, retry/backoff, delivery

receipts).

● Pipelines & E2E

○ Build pipeline test harnesses for AML pipelines (data-gen nightly, training weekly,

prediction/optimization) including orchestrated synthetic runs and fault injection

(missing slice, late competitor data, SB backlog).

○ Run E2E tests from raw data store -> ADLS -> AML -> RDBMS -> APIM/Frontend; assert

freshness SLOs and audit event completeness (Event Hubs -> ADLS immutable).

● Automation & Tooling

○ Develop Python-based automated tests (pytest) for data checks, model metrics, and API

contracts; integrate with Azure DevOps (pipelines, badges, gates).

○ Implement data-driven test runners (parameterized by site/material/model-version)

and store signed test artifacts alongside models in AML Registry.

○ Create synthetic test data generators and golden fixtures to cover edge cases (price

gaps, competitor shocks, cold starts).

● Reporting & Quality Ops

○ Publish weekly test reports and go/no-go recommendations for promotions; maintain a

defect taxonomy (data vs. model vs. serving vs. optimization).

○ Contribute to SLI/SLO dashboards (prediction timeliness, queue/DLQ, push success, data

drift) used for release gates.

Required Qualifications

○ 5–7+ years in QA with 3+ years focused on ML/Data systems (data pipelines + model validation).

○ Python automation (pytest, pandas, NumPy), SQL (PostgreSQL/Snowflake), and CI/CD (Azure

DevOps) for fully automated ML QA.

○ Strong grasp of ML validation: leakage checks, proper splits, metric selection

(MAE/MAPE/RMSE), drift detection, sensitivity/elasticity sanity checks.

○Experience testing AML pipelines (pipelines/jobs/components), and message-driven integrations

(Service Bus/Event Hubs).

○ API test skills (FastAPI/OpenAPI, contract tests, Postman/pytest- + idempotency and retry

patterns.

○ Familiar with feature stores/feature engineering concepts and reproducibility.

○Solid understanding of observability (App Insights/Log Analytics) and auditability requirements.

Education

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.

• Certification in Azure Data or ML Engineer Associate is a plus.

Job title: Data Science Intern- Remote

Report to: Data Science Manager in Pune

Job Responsibilities

• Solve Time series 1D (continuous glucose monitoring), RNA sequencing, and Computer vision (mainly medical images) problems
• Solve challenging problems using scalable 1D signal processing, machine learning, and deep learning approaches.
• In charge of developing state-of-the-art machine learning/deep learning algorithms for medical datasets
• Communicate highly technical results and methods concisely and clearly
• Collaborate with researchers in Japan to understand requirement as well request data.

Requirement

• Master/Ph.D. in relevant field from tier-1 colleges
• 1~2 years of experience with programming language/s Python or C++, Pandas
• 1~2 years of experience of working with deep learning framework, i.e. Pytorch or Tensorflow
• Well acquainted with classical time series problems-algorithms, NLP, Computer vision etc.
• Demonstrated experience with machine learning/deep learning models.
• Candidates should be able to read and implement research papers from top conferences.
• Develop IP (patents) and publish papers.
• Proficiency in Windows, Linux, dockers, PPT, and Git commands are highly required.

Preferred Skills

• Experience working with time-series, text, and sequential datasets in real world settings.
• Proven track record of research or industry experience on Time series problems, NLP, tabular datasets.
• Well acquainted with machine learning libraries such as pandas, scikit-learn etc.
• Experience programming in Azure or GCP or other cloud service.
• Publications in top-tier conferences will be a plus.

Location

This is a remote internship. If your performance is strong, we will consider converting your role to a full-time position after six months.

Job Description: Data Science Lead, Clinical Intelligence

Company Overview

Anervea is a pioneering AI transformation tech company delivering AI-powered SaaS solutions for the US pharma industry. Our therapy-agnostic clinical intelligence platform leverages real-world evidence (RWE) to predict patient outcomes and personalize treatments, empowering clients to optimize clinical trials and accelerate drug development.

Job Title

Data Science Lead, Clinical Intelligence

Location

Pune, India (hybrid office/remote) or fully remote within India.

Job Summary

We are seeking an experienced Data Science Lead to spearhead data operations for our clinical intelligence SaaS platform. You will lead data pipeline development, integrate computational biology insights, and ensure compliance with US pharma regulations, driving AI-powered predictions for patient outcomes across therapies (e.g., oncology, diabetes). This role is perfect for a leader with expertise in computational biology, clinical research, and scalable data systems.

Key Responsibilities

• Build and manage end-to-end data pipelines for ingesting and analyzing de-identified RWE, preclinical data, and public datasets (e.g., TCGA, ChEMBL) using Python, pandas, and cloud tools.
• Ensure data quality, privacy, and compliance with HIPAA, FDA (21 CFR Part 11), and GDPR, focusing on de-identification and bias mitigation.
• Lead integration of computational biology (e.g., genomics, AlphaFold protein modeling) into AI models for therapy-agnostic outcome predictions.
• Collaborate with AI teams to develop predictive models (e.g., XGBoost, PyTorch) for clinical trials and personalized medicine.
• Optimize data operations for scalability and cost-efficiency, handling large, diverse health datasets.
• Oversee cross-functional teams (remote/hybrid) to troubleshoot issues, audit data, and deliver client-ready insights.
• Stay ahead of US pharma trends (e.g., RWE, precision medicine) to enhance platform capabilities.

Qualifications and Requirements

• Master’s or PhD in Computational Biology, Bioinformatics, Data Science, or related field.
• 4+ years in data science or operations in US pharma/biotech, with expertise in clinical research (e.g., trials, RWE).
• Deep knowledge of computational biology (e.g., genomics, RDKit/AlphaFold for drug-protein interactions).
• Proficiency in Python, SQL, ETL tools (e.g., Airflow), and big data frameworks (e.g., Spark).
• Familiarity with US pharma regulations (HIPAA, FDA) and clinical trial processes (Phase 1-3).
• Experience with AI/ML for health data (e.g., scikit-learn, PyTorch).
• Based in India; open to remote or hybrid work in Pune.
• Strong leadership and communication skills for global client collaboration.

Preferred Skills

• Experience with cloud platforms (e.g., AWS, Azure) for secure data processing.
• Knowledge of SaaS platforms and API integrations for client data.
• Background in oncology or precision medicine (e.g., breast cancer outcome predictions).
• Expertise in mitigating data biases for fair AI predictions.

What We Offer

• Highly Competitive salary based on experience with performance bonuses.
• Flexible remote/hybrid work, health benefits, and learning opportunities.
• Leadership role in cutting-edge US pharma AI innovation with travel opportunities in the US
• Collaborative, global team environment.

About Client:

Our client is a Palo Alto–based AI infrastructure and talent platform founded in 2018. It helps companies connect with remote software developers using AI-powered vetting and matching technology. Originally branded as the “Intelligent Talent Cloud,”enabled companies to “spin up their engineering dream team in the cloud” by sourcing and managing vetted global talent.

In recent years, they have evolved to support AI infrastructure and AGI workflows, offering services in model training, fine-tuning, and deployment—powered by their internal AI platform, ALAN, and backed by a vast talent network. They reported $300 million in revenue and reached profitability. Their growth is driven by demand for annotated training data from AI labs, including major clients like OpenAI, Google, Anthropic, and Meta.

Job Title: Machine Learning Engineer

Location: Pan India

Experience: 5+ yrs

Employment Type: Contract to hire

Work Mode: Remote

Notice Period: Immediate joiners

Job Description:-

Requirements:

• Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
• 3+ years of hands-on ML development experience
• Proficiency in at least some of the ML areas and frameworks, including:
• Supervised learning (classification, regression, …)
• Unsupervised learning (clustering, anomaly detection, …)
• Time-series analysis
• Natural Language Processing (NLP)
• Computer Vision (CV)
• Statistical modeling
• Ability to understand and apply different models to real-world use cases
• Hands-on experience with DS and ML solutions in production environments
• Strong understanding of data cleaning and wrangling, feature engineering, model optimization, and evaluation metrics
• Proficiency in Python and its common data science libraries (e.g., Pandas, NumPy, Scikit-learn)

Preferred Qualifications:

• Proven expertise in Deep learning (e.g., convolutional neural networks, recurrent neural networks, transformers).
• Experience with cloud data platforms (Databricks, AWS, etc.)
• Knowledge of MLOps principles and tools for model deployment and monitoring
• Hands-on experience with PySpark and Databricks Platform
• Stay up-to-date with the latest advancements in machine learning and artificial intelligence.
• Bonus: Experience and knowledge in Kaggle competitions and Benchmarks, such as MLEBench

We are seeking a Machine Learning Researcher to join our team. You will be working on cutting-edge research projects, building experimental prototypes, and documenting your findings through technical publications. This is a fully remote position, initially a 3-month research engagement with the potential for extension or full-time offer based on performance and research contributions. This is a paid position at ₹15,000-20,000/month .

This is an exciting opportunity to work in a dynamic research environment and contribute to advancing the field of AI development. This is a completely remote role where you will work on your own schedule. No micro-management, promise.

You will be learning cutting-edge techniques and contributing to original research, so don't worry if you do not meet all qualifications. As long as you can learn, adapt, and think critically about research problems, this will be a valuable experience for you.

Responsibilities

• Research and implement advanced techniques like LoRA, Fine-Tuning, Transfer Learning, RLHF, GRPO, and emerging training methodologies in experimental settings.
• Read and analyze recent research papers, reproduce key findings, and contribute to our understanding of state-of-the-art AI concepts.
• Design and conduct experiments for client-facing research projects under guidance of senior researchers.
• Document your research journey by writing technical articles and research summaries that explain complex AI topics and your experimental findings.
• Contribute to model training pipelines and evaluate novel approaches for improving model performance.

Qualifications

• Strong foundation in machine learning research or similar experience, with focus on NLP and deep learning.
• Excellent programming skills with proven experience implementing Python-based research solutions.
• Proficiency with research-essential libraries (NumPy, pandas, scikit-learn) and experimental frameworks.
• Experience with ML research frameworks (PyTorch, TensorFlow, Keras), text embeddings, and transformer architectures.
• No degree required - if you have research aptitude and technical skills, we'd love to work with you.
• Excellent written and verbal communication skills for research documentation.
• Strong analytical and research methodology skills to design experiments and validate findings.
• Ability to read, understand, and implement techniques from AI research papers.
• Understanding math is a huge plus; topics like topology and linear algebra are very helpful on the job

Bonus Experience

• LLMs and research tooling: Advanced agents, GPT variants, Langchain, HuggingFace research tools, etc.
• Modern training techniques: Reinforcement Learning from Human Feedback (RLHF), Constitutional AI, preference learning.
• Deep learning research, reinforcement learning, generative models, and multi-modal AI systems.

Interview Process (<3 days)

• 1 x Phone Screen | 10 mins
• 1 x Technical Research Interview | 1 hour

Note: This is a 3-month research position, with the potential to transition into a full-time research role.

We don't hire based on DSA. You'll be a good fit if you're passionate about AI research and capable of building experimental applications and conducting meaningful research. We prefer people who are strong in AI fundamentals, research methodology, and open to exploring any framework/library as required for their research.

Degrees are redundant. First-time researchers and recent graduates are encouraged to apply. Will hire based on research potential and curiosity. Work from wherever, whenever. Immediate joiners only.