Data Scientist

HCLTech

0 years

0 Lacs

Chennai Tamil Nadu India

Posted:4 hours ago| Platform:

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Skills Required

data learning design analysis preprocessing engineering model development optimization programming ml testing regression aws azure power sql querying relational apache processing vision etl pipeline tensorflow pytorch keras numpy matplotlib mysql postgresql mongodb tableau

Work Mode

On-site

Job Type

Full Time

Job Description

Machine Learning Engineer

Required Skills:

Programming Languages
: Strong proficiency in
Python
, with experience in
SQL
.
Machine Learning
: Hands-on experience with
Scikit-learn
,
TensorFlow
,
Keras
,
PyTorch
, or similar ML libraries.
Data Analysis
: Strong skills in
Pandas
,
NumPy
, and
Matplotlib
for data manipulation and analysis.
Statistical Analysis
: Experience applying statistical methods to data, including hypothesis testing and regression analysis.
Cloud Platforms
: Familiarity with
AWS
,
Azure
, or
Google Cloud
for deploying models and using cloud-native data services (e.g.,
AWS Sagemaker
,
Azure ML
).
Data Visualization
: Experience using
Tableau
,
Power BI
,
Matplotlib
,
Seaborn
, or
Plotly
for creating visualizations.
SQL & Databases
: Proficiency in
SQL
for querying relational databases and working with
NoSQL
databases (e.g.,
MongoDB
,
BigQuery
).
Version Control
: Experience using
Git
for version control.

Desirable Skills:

Big Data Technologies
: Familiarity with tools like
Apache Hadoop
,
Spark
,
Dask
, or
Google BigQuery
for processing large datasets.
Deep Learning
: Experience with deep learning frameworks such as
TensorFlow
,
PyTorch
, or
MXNet
.
NLP & Computer Vision
: Experience with natural language processing (NLP) using
spaCy
,
NLTK
, or
transformers
, and computer vision using
OpenCV
or
TensorFlow
.
MLOps
: Familiarity with MLOps tools like
Kubeflow
,
MLflow
, or
DVC
for managing model workflows.
Data Engineering
: Experience with ETL tools like
Apache Airflow
,
Talend
,
AWS Glue
, or
Google Dataflow
for data pipeline automation.

Tools & Technologies:

Machine Learning
: Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost.
Data Analysis
: Pandas, NumPy, Matplotlib, Seaborn, Plotly.
Cloud Platforms
: AWS, Google Cloud, Azure.
Databases
: MySQL, PostgreSQL, MongoDB, BigQuery, Snowflake.
Data Visualization
: Tableau, Power BI, Matplotlib, Seaborn, Plotly.
Version Control
: Git.

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