BD&I ML Engineer

Description:

Must have skills:

Python azure data factory Databricks Apache Spark / PySpark Azure Data Lake Store Azure Data Lake Analytics Pipeline Execution/ETL Machine Learning AI ETL clould data pipelines Docker Kubernetes AWS

Requirements:

About the Role

We are seeking a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will be responsible for developing and implementing machine learning models to solve real-world problems and drive business value. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy innovative solutions.

Key Responsibilities

Design, develop, and implement machine learning models for various applications, such as predictions, customer churn analysis, and fraud detection.Collect, clean, and preprocess large datasets for training and evaluation.

Conduct exploratory data analysis and feature engineering to improve model performance.

Evaluate and select appropriate machine learning algorithms and techniques based on business requirements and data characteristics.

Develop and maintain machine learning pipelines for data ingestion, preprocessing, training, and deployment.

Monitor and optimize the performance of deployed models in production.

Stay up-to-date with the latest advancements in machine learning and related technologies.

Collaborate with cross-functional teams to integrate machine learning solutions into existing systems

Communicate technical concepts and findings to both technical and non-technical audiences.

Stay abreast of the latest advancements in data science and machine learning techniques.

Mentor and guide junior data scientists, fostering a collaborative and knowledge-sharing environment.

What You Bring

Experience:

2 to 3 years of experience in developing and deploying machine learning models in a professional setting.

Telecom industry experience is highly preferred.

Technical Skills:

Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.

Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

Building & deploying model using python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture.

Excellent problem-solving and analytical skills.

Communication and collaboration skills.

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

3+ years of experience in developing and deploying machine learning models in a professional setting.

Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.

Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

Excellent problem-solving and analytical skills.

Strong communication and collaboration skills.

Soft Skills:

Strong problem-solving and critical thinking skills

Ability to break down complex technical topics for business stakeholders

Comfortable working in a fast-paced, agile environment with shifting priorities

Qualifications:

Bachelor's degree in Computer Science or related field.

Master's degree or equivalent advanced degree preferred.

Proven track record of delivering data science projects from ideation to production.

Strong communication skills and the ability to tell compelling stories with data.

Comfortable with both structured and unstructured data sets.

Job Responsibilities:

About the Role

We are seeking a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will be responsible for developing and implementing machine learning models to solve real-world problems and drive business value. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy innovative solutions.

Key Responsibilities

Design, develop, and implement machine learning models for various applications, such as predictions, customer churn analysis, and fraud detection.Collect, clean, and preprocess large datasets for training and evaluation.

Conduct exploratory data analysis and feature engineering to improve model performance.

Evaluate and select appropriate machine learning algorithms and techniques based on business requirements and data characteristics.

Develop and maintain machine learning pipelines for data ingestion, preprocessing, training, and deployment.

Monitor and optimize the performance of deployed models in production.

Stay up-to-date with the latest advancements in machine learning and related technologies.

Collaborate with cross-functional teams to integrate machine learning solutions into existing systems

Communicate technical concepts and findings to both technical and non-technical audiences.

Stay abreast of the latest advancements in data science and machine learning techniques.

Mentor and guide junior data scientists, fostering a collaborative and knowledge-sharing environment.

What You Bring

Experience:

2 to 3 years of experience in developing and deploying machine learning models in a professional setting.

Telecom industry experience is highly preferred.

Technical Skills:

Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.

Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

Building & deploying model using python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture.

Excellent problem-solving and analytical skills.

Communication and collaboration skills.

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

3+ years of experience in developing and deploying machine learning models in a professional setting.

Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.

Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

Excellent problem-solving and analytical skills.

Strong communication and collaboration skills.

Soft Skills:

Strong problem-solving and critical thinking skills

Ability to break down complex technical topics for business stakeholders

Comfortable working in a fast-paced, agile environment with shifting priorities

Qualifications:

Bachelor's degree in Computer Science or related field.

Master's degree or equivalent advanced degree preferred.

Proven track record of delivering data science projects from ideation to production.

Strong communication skills and the ability to tell compelling stories with data.

Comfortable with both structured and unstructured data sets.

What We Offer:

Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them.

Collaborative Environment: You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities

Work-Life Balance: GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays.

Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training(GL Vantage, Toast Master),Stress Management program, professional certifications, and technical and soft skill trainings.

Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Group Term Life Insurance, Group Personal Accident Insurance , NPS(National Pension Scheme ), Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses.

Fun Perks: We want you to love where you work, which is why we host sports events, cultural activities, offer food on subsidies rates, Corporate parties. Our vibrant offices also include dedicated GL Zones, rooftop decks and GL Club where you can drink coffee or tea with your colleagues over a game of table and offer discounts for popular stores and restaurants