HCLTech Mega Walk in Drive

Date : Aug 22

Location - Bangalore

Hyderabad

Chennai

Experience - 5 years to 13 years

Please mark your attendance for the Walkin Drive below

QRCode for Attendance Confirmation- Mega Drive - 22nd Aug'26- Data&AI; (1) 2.png

Job Overview:

We are seeking a skilled Machine Learning Engineer , Data Scientist , or Data Analyst to design, develop, and deploy machine learning models, conduct deep data analysis, and generate actionable insights. The ideal candidate will have experience in data preprocessing, feature engineering, model development, and performance optimization, working with large datasets and leveraging advanced machine learning frameworks.

Key Responsibilities

- :Data Preparation & Analysi s
- :Gather, clean, and preprocess structured, semi-structured, and unstructured data from various sources
- .Conduct exploratory data analysis (EDA) to identify trends, patterns, and outliers
- .Apply data wrangling techniques using Panda s, NumP y, and SQ L to transform raw data into usable formats
- .Use statistical analysis to drive data-driven decision-making
- .Machine Learning Model Developmen t
- :Build, train, and fine-tune machine learning models using Scikit-lear n, TensorFlo w, Kera s, or PyTorc h
- .Develop predictive models, classification algorithms, clustering models, and recommendation systems
- .Conduct hyperparameter optimization using techniques like grid search or random search
- .Model Evaluation & Optimizatio n
- :Evaluate model performance using metrics such as Accurac y, Precisio n, Recal l, F1-Scor e, AUC-RO C, Confusion Matri x, and Cross-validatio n
- .Improve model performance through techniques such as feature engineering, data augmentation, and regularization
- .Deploy models into production environments,



and monitor performance for continual improvement
- .Data Visualization & Reportin g
- :Develop dashboards and reports using Tablea u, Power B I, Matplotli b, Seabor n, or Plotl y
- .Present findings through explicit visualizations and actionable insights to non-technical stakeholders
- .Write detailed reports on data analysis and machine learning results, ensuring transparency and reproducibility
- .Collaboration & Stakeholder Communicatio n
- :Work closely with cross-functional teams (e.g., engineering, product, business) to define data-driven solutions
- .Communicate technical concepts clearly to non-technical stakeholders and provide insights that influence product and business strategy
- .Data Pipeline & Automatio n
- :Design and implement scalable data pipelines for model training and deployment using Airflo w, Apache Kafk a, or Celer y
- .Automate data collection, preprocessing, and feature extraction tasks
- .Research & Continuous Learnin g
- :Stay up-to-date with the latest trends in machine learning, deep learning, and data science methodologies
- .Explore new tools, techniques, and frameworks to improve model accuracy and efficiency

.

Required Skill

- s:Programming Languag es: Strong proficiency in Pyth on, with experience in S Q
- L.Machine Learni ng: Hands-on experience with Scikit-lea rn, TensorFl ow, Ker as, PyTor ch, or similar ML librarie
- s.Data Analys is: Strong skills in Pand as, Num Py,



and Matplotl ib for data manipulation and analysi
- s.Statistical Analys is: Experience applying statistical methods to data, including hypothesis testing and regression analysi
- s.Cloud Platfor ms: Familiarity with A WS, Azu re, or Google Clo ud for deploying models and using cloud-native data services (e.g., AWS Sagemak er, Azure ML
- ).Data Visualizati on: Experience using Table au, Power BI, Matplotl ib, Seabo rn, or Plot ly for creating visualization
- s.SQL & Databas es: Proficiency in S QL for querying relational databases and working with NoS QL databases (e.g., Mongo DB, BigQue ry
- ).Version Contr ol: Experience using G it for version contro

l.

Desirable Skil

- ls:Big Data Technolog ies: Familiarity with tools like Apache Had oop, Sp ark, D ask, or Google BigQu ery for processing large datase
- ts.Deep Learn ing: Experience with deep learning frameworks such as TensorF low, PyTo rch, or MX N
- et.NLP & Computer Vis ion: Experience with natural language processing (NLP) using sp aCy, N LTK, or transform ers, and computer vision using Ope nCV or TensorF l
- ow.ML Ops: Familiarity with MLOps tools like Kubef low, MLf low, or DVC for managing model workflo
- ws.Data Engineer ing: Experience with ETL tools like Apache Airf low, Tal end, AWS G lue, or Google Dataf low for data pipeline automati

on.

Tools & Technolog

- ies:Machine Lear ning: Scikit-l earn, Tensor Flow, PyT orch, K eras, XGB o
- ost.Data Anal ysis: Pa ndas, N umPy, Matplo tlib, Sea born, Pl o
- tly.Cloud Platf orms: AWS, Google C loud, A z
- ure.Datab ases: M ySQL, Postgr eSQL, Mon goDB, BigQ uery, Snowf l
- ake.Data Visualiza tion: Tab leau, Powe r BI, Matplo tlib, Sea born, Pl o
- tly.Version Con trol:

Git.

📌 Mega Walkin Drive - AIML (Bangalore Metropolitan Area)
🏢 HCLTech
📍 Bangalore Metropolitan Area