data science trainer at Technobrilliant Learning Solutions · Pune · 1 - 4 years · ₹15000L - ₹450000L / yr · Profitable · Posted 25 Dec 2024

Role Description
This is a full-time on-site role for a Data Science Trainer at Technobrilliant Learning Solutions in Pune. The Data Science Trainer will be responsible for conducting science education classes, teaching physics and mathematics concepts, creating lesson plans, and delivering high-quality education to students.
Qualifications
- Qualified Teacher with expertise in lesson planning
- Strong communication and presentation skills
- Ability to engage and motivate students
- Bachelor's or Master's degree in a relevant field (e.g., Data Science, Computer Science)
- Experience in data science or related industry is a plus

About Technobrilliant Learning Solutions
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Data Science (SME)
FACE Prep is India’s leading employability and industry-aligned education company. For over 17 years, we have partnered with higher education institutions to bridge the gap between academia and industry.
● Worked with 2,000+ colleges and universities across India
● Trained 6+ million students across disciplines
● Market leaders in:
● Employability skills & placement readiness
● Industry-aligned academic papers(credit-bearing)
● Full-scale industry-aligned degree programs with universities
● Pan-India operations, headquartered in Coimbatore
● Young, energetic, mission-driven team
● Fast-growing organization with headcount expected to cross 1,000 employees in the next financial year
At FACE Prep, people are the platform on which outcomes are built.
Position: Data Science (SME)
Location: Coimbatore
Duration: Full-Time
Department: Training & Development
Experience: Minimum 2 Years
Role Description :
The Data Science Subject Matter Expert (SME) is a full-time, on-site role based in Coimbatore. The SME will design and deliver data science curricula, including lectures, hands-on labs, and project-based learning for students preparing for tech careers. Daily responsibilities include creating educational content, developing problem sets and case studies, mentoring learners on data analysis and model-building, and reviewing student work to provide constructive feedback. The SME will collaborate with other trainers and the product team to align content with current industry practices and hiring requirements. The role also involves analyzing learner performance data, refining teaching strategies, and occasionally contributing to workshops, bootcamps, and online learning materials.
Requirements:
• Strong foundation in Statistics and Data Science, with the ability to explain complex concepts clearly and practically.
• Hands-on experience in Data Analytics and Data Analysis, including working with real-world datasets and deriving actionable insights.
• Excellent Analytical Skills for problem-solving, designing assignments, and guiding learners through data-driven decision-making.
• Proficiency in common data science tools and languages (e.g., Python/R, SQL, data visualization tools such as Tableau/Power BI).
• Prior experience in teaching, mentoring, corporate training, or curriculum development is highly beneficial.
• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Data Science, or related discipline.
• Ability to communicate effectively with diverse learner groups and collaborate within a multidisciplinary team.
• Exposure to machine learning concepts, model evaluation, and deployment practices is a plus.
IMMEDIATE JOINERS REQUIRED
Key Responsibilities
Strong understanding of Machine Learning algorithms (supervised and unsupervised)
Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)
Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)
Solid knowledge of Statistics, probability, and data analysis methods
Proficiency in SQL for querying relational databases
Strong programming skills in Python (or similar languages)
Excellent communication skills with the ability to explain complex concepts simply
Required Qualifications
3+ years of hands-on experience as a Data Scientist or in a similar role.
Strong expertise in classical machine learning and regression modeling.
Solid understanding of statistics, including probability, distributions, hypothesis testing,
and correlation analysis.
Proficiency in Python with libraries such as: scikit-learn pandas NumPy
Experience working with structured/tabular data.
Strong problem-solving and analytical thinking skills.
Ability to clearly explain models and results to non-technical stakeholders.
Role Overview
As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact.
Key Responsibilities
Data Science & Machine Learning
- Analyze structured and unstructured data to identify patterns, trends, and business opportunities.
- Perform exploratory data analysis (EDA), feature engineering, and data preparation.
- Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.
- Apply statistical techniques to solve business problems and validate model performance.
- Design and execute experiments to improve model accuracy and business outcomes.
AI Solution Development
- Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.
- Translate business requirements into scalable data science approaches.
- Contribute to Generative AI and advanced analytics initiatives where applicable.
- Document methodologies, model performance, and key findings.
Required Technical Skills
- Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.
- Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.
- Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.
- Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.
- Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.
- Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.
- Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.
- Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.
- Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 2–4 years of experience developing machine learning or data science solutions.
- Experience working on end-to-end data science projects in a business environment.
Nice to Have
- Exposure to Generative AI, LLMs, RAG, or Agentic AI.
- Experience with Computer Vision or Natural Language Processing (NLP).
- Familiarity with cloud-based AI platforms.
- Knowledge of construction, engineering, manufacturing, or industrial domains.
- Participation in hackathons, research, Kaggle competitions, or open-source projects.
Soft Skills
Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Sr.Data Scientist,Python, AI ML
We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.
Hiring for Data Scientist / Senior Data Scientist
Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.
🚀 We’re Hiring | Data Scientist 🧠📊
Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!
🔹 Experience: 8+ Years
🔹 Must-Have Skills:
🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization
📍 Location: Pune
💼 Work Mode: Work from Office
If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!
📩 Interested? Kindly text
#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow
We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.
Key Responsibilities
- Develop and implement machine learning and predictive analytics models.
- Perform data analysis, statistical modeling, and optimization to solve business problems.
- Build demand forecasting and predictive models using time-series and other advanced techniques.
- Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.
- Develop and maintain scalable data pipelines for ML model development and deployment.
- Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.
- Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.
- Validate models for accuracy, robustness, bias, and production readiness.
- Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.
Required Skills
- Python
- SQL
- Data Science & Machine Learning
- Predictive Modeling
- Statistical Analysis
- Machine Learning Algorithms
- Optimization Techniques
- Google Cloud Platform (GCP)
- BigQuery
- Dataflow
- Dataproc
- Data Fusion
- Cloud SQL
- Airflow
- PySpark
- PostgreSQL
- Terraform
- Tekton
- APIs
- MLOps
Preferred Skill
- Java
Good to Have
- Demand Forecasting
- Time-Series Analysis
- Neural Networks
- Ensemble Methods
- Support Vector Machines (SVM)
- Regression and Cluster Analysis
- ML Model Testing
- Bias Detection and Data Drift Monitoring
- Production ML Deployment
- QlikSense
- Automotive or Supply Chain Analytics
Education
Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.
We are looking for a hands-on Lead Data Scientist with strong analytical, machine learning, and problem-solving skills to work in a client-facing environment.
The role requires someone who can independently identify opportunities, formulate hypotheses, design solutions, and drive initiatives from analysis through experimentation and production implementation. The candidate should also be comfortable guiding team members and working closely with engineering and client stakeholders.
Responsibilities:
- Analyse complex datasets to identify patterns, issues, and opportunities.
- Formulate and validate hypotheses through structured analysis and experimentation.
- Build and improve machine learning and anomaly detection solutions.
- Design end-to-end solutions considering data, modelling, engineering, and production constraints.
- Perform root cause analysis across models, data, and systems.
- Work with engineering teams on feature pipelines, model inference, and production deployment.
- Lead technical discussions with clients and communicate recommendations, trade-offs, and expected impact.
- Guide team members on analysis, modelling, and solution design.
- Proactively identify initiatives and roadmap items that can add value to the project.
Requirements:
- Strong foundation in statistics and machine learning.
- Strong hands-on experience with Python and SQL.
- Hands-on experience with Python ML and data frameworks such as Pandas, NumPy, scikit-learn, TensorFlow/Keras, Dask, Matplotlib, Boto3 SageMaker Python SDK, and Horovod.
- Strong data analysis, hypothesis-generation, and problem-solving skills.
- Experience with standard supervised and unsupervised ML techniques.
- Experience with anomaly detection techniques such as Isolation Forest and Autoencoders.
- Experience building and deploying production ML solutions.
- Working knowledge of data engineering and real-time / batch inference environments.
- Strong communication and stakeholder-management skills.
- Ability to lead technical work and guide cross-functional teams.
Good to Have:
- Experience in fraud detection or risk modelling.
- Experience with Graph Neural Networks.
- Exposure to real-time systems, streaming features, and low-latency data stores.
- Experience in AdTech, e-commerce, gaming, mobile applications, or similar high-volume consumer platforms.
Role Overview
We are looking for a passionate Computer Science Faculty to train and mentor students in computer
science concepts and practical applications while helping them develop industry-relevant technical skills.
Key Responsibilities
• Conduct hands-on practical training sessions in Computer Science.
• Explain programming and technical concepts through practical applications.
• Conduct coding exercises, assignments, projects, and assessments.
• Monitor student attendance, assessment scores, assignment performance, and learning progress.
• Provide continuous technical mentoring and guidance.
• Help students develop industry-relevant technical skills.
• Assist students in obtaining certifications in high-demand technologies.
• Support students in securing internships and provide continuous guidance.
• Keep students updated with relevant industry trends and technologies.
• Ensure students achieve periodic learning targets and outcomes.
• Work effectively in a corporate-style training environment.
Preferred Candidates
• Prior Computer Science teaching/training experience preferred.
• Strong technical and programming knowledge.
• Strong communication and presentation skills.
• Good classroom management skills.
• Passion for teaching and mentoring students.
• Immediate joiners preferred
Qualification
• PG qualification in Computer Science
• UGC NET/SET in Computer Science OR completed PhD in Computer Science / relevant specialization
This is a remote position.
About Leegality:
Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.
We have multiple products across 2 categories:
Document Infrastructure:
Products that help businesses build paperless processes at scale:
- Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
- Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contract
- Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner
Consent Infrastructure:
- Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
- Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.
If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.
Curious about our impact? Explore our customer success stories: leegality.com/case-studies
Our Culture
At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.
We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:
- Flexible working hours
- Hybrid work setup
- Bi-annual performance appraisals
- A culture that rewards initiative, curiosity, and impact
If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.
Location: Hybrid
Job Brief:
- As a Machine Learning Engineer specializing in Computer Vision (CV) and Natural Language Processing (NLP), you will develop solutions to interesting technical problems, exploring exciting growth opportunities and having a real impact on our product, particularly focusing on document and content intelligence.
- To ensure success, you should demonstrate solid data science knowledge and experience in a related ML, CV, or NLP role. A first-class engineer will be someone whose expertise enhances our systems for document intelligence and content processing
Responsibilities:
- Designing machine learning systems, self-running artificial intelligence (AI) software, and specialized models for Computer Vision and Natural Language Processing applications.
- Transforming data science prototypes and applying appropriate deep learning algorithms and tools to text and image/document data.
- Solving complex CV and NLP problems with multi-layered data types, such as image/document classification, information extraction, semantic search, and object detection.
- Optimizing existing machine learning models, with a focus on high-performance model deployment for CV and NLP tasks.
- Developing ML algorithms (including large language models/LLMs and computer vision models) to analyze huge volumes of historical text, image, and document data to make predictions and automate workflows.
- Running tests, performing statistical analysis, and interpreting test results for CV/NLP model performance.
- Documenting machine learning processes, model architectures, and data pipelines.
- Keeping abreast of developments in machine learning, Computer Vision, and Natural Language Processing.
Requirements:
- 3+ years of relevant experience in Machine Learning Engineering, with a strong focus on Computer Vision and/or Natural Language Processing.
- Advanced proficiency with Python.
- Extensive knowledge of ML frameworks, libraries (e.g., PyTorch, Transformers), data structures, data modeling, and software architecture.
- Experience with building and maintaining scalable RESTful APIs (e.g., FastAPI).
- In-depth knowledge of mathematics, statistics, deep learning (CNNs, RNNs, Transformers), and algorithms.
- Superb analytical and problem-solving abilities, especially for unstructured data challenges.
- Great communication and collaboration skills.
- Excellent time management and organizational abilities.
- Experience with cloud platforms (e.g., AWS) for model deployment and MLOps.
Recruitment Process:
- Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
- You will be contacted via email with the next steps upon being shortlisted.
- The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
- Final selection and CTC will be based on your overall performance and experience.
Apply directly through our career page: https://careers.leegality.com/jobs/Careers
For more information about us please visit our:
Our Company and Culture: https://bit.ly/3Iqm5SB
Our Website: www.leegality.com/
Our LinkedIn Page: www.linkedin.com/company/leegality/
Leegality's Privacy Notice: https://www.leegality.com/employee-privacy-notice











