Data Scientist

Data Havn

Data Scientist

Infinium Associate

Company

Home

Data Scientist

at Data Havn

Agency job

via Infinium Associate

4 - 6 yrs

₹40L - ₹45L / yr

Delhi, Gurugram, Noida, Ghaziabad, Faridabad

Skills

R Programming

Google Cloud Platform (GCP)

Data Science

Python

Data Visualization

Big Data

Data Structures

Natural Language Processing (NLP)

DataHavn IT Solutions is a company that specializes in big data and cloud computing, artificial intelligence and machine learning, application development, and consulting services. We want to be in the frontrunner into anything to do with data and we have the required expertise to transform customer businesses by making right use of data.

About the Role:

As a Data Scientist specializing in Google Cloud, you will play a pivotal role in driving data-driven decision-making and innovation within our organization. You will leverage the power of Google Cloud's robust data analytics and machine learning tools to extract valuable insights from large datasets, develop predictive models, and optimize business processes.

Key Responsibilities:

Data Ingestion and Preparation:
Design and implement efficient data pipelines for ingesting, cleaning, and transforming data from various sources (e.g., databases, APIs, cloud storage) into Google Cloud Platform (GCP) data warehouses (BigQuery) or data lakes (Dataflow).
Perform data quality assessments, handle missing values, and address inconsistencies to ensure data integrity.
Exploratory Data Analysis (EDA):
Conduct in-depth EDA to uncover patterns, trends, and anomalies within the data.
Utilize visualization techniques (e.g., Tableau, Looker) to communicate findings effectively.
Feature Engineering:
Create relevant features from raw data to enhance model performance and interpretability.
Explore techniques like feature selection, normalization, and dimensionality reduction.
Model Development and Training:
Develop and train predictive models using machine learning algorithms (e.g., linear regression, logistic regression, decision trees, random forests, neural networks) on GCP platforms like Vertex AI.
Evaluate model performance using appropriate metrics and iterate on the modeling process.
Model Deployment and Monitoring:
Deploy trained models into production environments using GCP's ML tools and infrastructure.
Monitor model performance over time, identify drift, and retrain models as needed.
Collaboration and Communication:
Work closely with data engineers, analysts, and business stakeholders to understand their requirements and translate them into data-driven solutions.
Communicate findings and insights in a clear and concise manner, using visualizations and storytelling techniques.

Required Skills and Qualifications:

Strong proficiency in Python or R programming languages.
Experience with Google Cloud Platform (GCP) services such as BigQuery, Dataflow, Cloud Dataproc, and Vertex AI.
Familiarity with machine learning algorithms and techniques.
Knowledge of data visualization tools (e.g., Tableau, Looker).
Excellent problem-solving and analytical skills.
Ability to work independently and as part of a team.
Strong communication and interpersonal skills.

Preferred Qualifications:

Experience with cloud-native data technologies (e.g., Apache Spark, Kubernetes).
Knowledge of distributed systems and scalable data architectures.
Experience with natural language processing (NLP) or computer vision applications.
Certifications in Google Cloud Platform or relevant machine learning frameworks.

About the Role:

Key Responsibilities:

Data Ingestion and Preparation:
Design and implement efficient data pipelines for ingesting, cleaning, and transforming data from various sources (e.g., databases, APIs, cloud storage) into Google Cloud Platform (GCP) data warehouses (BigQuery) or data lakes (Dataflow).
Perform data quality assessments, handle missing values, and address inconsistencies to ensure data integrity.
Exploratory Data Analysis (EDA):
Conduct in-depth EDA to uncover patterns, trends, and anomalies within the data.
Utilize visualization techniques (e.g., Tableau, Looker) to communicate findings effectively.
Feature Engineering:
Create relevant features from raw data to enhance model performance and interpretability.
Explore techniques like feature selection, normalization, and dimensionality reduction.
Model Development and Training:
Develop and train predictive models using machine learning algorithms (e.g., linear regression, logistic regression, decision trees, random forests, neural networks) on GCP platforms like Vertex AI.
Evaluate model performance using appropriate metrics and iterate on the modeling process.
Model Deployment and Monitoring:
Deploy trained models into production environments using GCP's ML tools and infrastructure.
Monitor model performance over time, identify drift, and retrain models as needed.
Collaboration and Communication:
Work closely with data engineers, analysts, and business stakeholders to understand their requirements and translate them into data-driven solutions.
Communicate findings and insights in a clear and concise manner, using visualizations and storytelling techniques.

Required Skills and Qualifications:

Strong proficiency in Python or R programming languages.
Experience with Google Cloud Platform (GCP) services such as BigQuery, Dataflow, Cloud Dataproc, and Vertex AI.
Familiarity with machine learning algorithms and techniques.
Knowledge of data visualization tools (e.g., Tableau, Looker).
Excellent problem-solving and analytical skills.
Ability to work independently and as part of a team.
Strong communication and interpersonal skills.

Preferred Qualifications:

Experience with cloud-native data technologies (e.g., Apache Spark, Kubernetes).
Knowledge of distributed systems and scalable data architectures.
Experience with natural language processing (NLP) or computer vision applications.
Certifications in Google Cloud Platform or relevant machine learning frameworks.

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