Data Scientist at Srijan Technologies · Remote only · 3 - 8 years · ₹10L - ₹25L / yr (ESOP available) · Profitable · Remote only · Posted 20 Dec 2021

Job Responsibilities:-
- Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
- Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
- Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
- Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
- Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
- Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
- Experience working with big data systems and big data concepts.
- Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
- Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
- Experience with noisy and/or unstructured textual data.
knowledge graph and NLP including summarization, topic modelling etc
- Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
- Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
- Strong understanding of text pre-processing and normalization techniques, such as tokenization,
- POS tagging and parsing and how they work at a low level.
- Excellent problem solving skills.
- Strong verbal and written communication skills
- Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
- Practical experience in using NLP related techniques and algorithms
- Experience in open source coding and communities desirable.
Able to containerize Models and associated modules and work in a Microservices environment

About Srijan Technologies
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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.
About Nexora Group
Nexora Group is a technology and innovation-driven organization dedicated to building intelligent solutions that leverage Artificial Intelligence, Machine Learning, Data Analytics, and emerging technologies. We are committed to fostering talent by providing aspiring professionals with practical exposure, mentorship, and opportunities to work on real-world projects.
Internship Overview
Nexora Group is looking for enthusiastic and driven AI/ML Interns to join our team. This internship is ideal for students and recent graduates who are passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Interns will gain hands-on experience working on real-world AI projects, developing intelligent models, and solving complex business challenges using data-driven approaches.
Key Responsibilities
- Assist in developing, training, and evaluating Machine Learning models.
- Collect, clean, and preprocess datasets for AI/ML applications.
- Conduct exploratory data analysis and feature engineering.
- Work on Deep Learning, Natural Language Processing (NLP), and Computer Vision projects.
- Research and implement AI algorithms and emerging technologies.
- Support the development of Generative AI and Large Language Model (LLM)-based solutions.
- Optimize model performance and evaluate results using industry-standard metrics.
- Document project workflows, findings, and technical reports.
- Collaborate with cross-functional teams to develop innovative AI solutions.
Required Skills
- Basic understanding of Machine Learning and Artificial Intelligence concepts.
- Knowledge of Python programming.
- Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.
- Understanding of data structures, algorithms, and statistics.
- Basic knowledge of Deep Learning, NLP, or Computer Vision concepts.
- Strong analytical and problem-solving skills.
- Good communication and teamwork abilities.
- Willingness to learn and adapt to new technologies.
Preferred Qualifications
- Experience with AI/ML projects, hackathons, or research work.
- Knowledge of Generative AI, Prompt Engineering, and LLMs.
- Familiarity with cloud platforms and AI deployment tools.
- Certifications in AI, Machine Learning, or Data Science are a plus.
- GitHub projects or portfolio showcasing AI/ML work.
Eligibility
- Undergraduate or postgraduate students pursuing Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related fields.
- Recent graduates seeking practical industry experience.
- Candidates with a strong interest in AI innovation and research.
What You'll Gain
- Hands-on experience with real-world AI and Machine Learning projects.
- Mentorship from experienced AI professionals.
- Exposure to cutting-edge AI tools, frameworks, and technologies.
- Internship Completion Certificate.
- Letter of Recommendation based on performance.
- Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
- Professional networking and career development opportunities.






