The demand for data scientists has reached unprecedented levels in the age of artificial intelligence and big data. MNCs are at the forefront of this surge, offering lucrative opportunities for professionals in data science. Below, we explore five of the top data science vacancies in MNCs like Microsoft, ProArch, People Prime Worldwide, EPAM Systems, and Accellor.
Microsoft is one of the leading tech companies in the world, continuously pushing the boundaries of AI, cloud computing, and data science. For their Data Scientist 2 role, the company seeks engineers who are passionate about smart growth, high efficiency, and delivering a trusted experience to customers. This position is ideal for those interested in large-scale cloud solutions, especially within Microsoft’s Azure ecosystem.
Responsibilities:
a. Analyze large-scale Azure data to address critical business problems.
b. Develop new software features within advanced visualizations.
c. Work on mission-critical solutions utilizing multiple Azure services.
d. Design and implement production-level data science code in a collaborative team environment.
Qualifications:
a. Bachelor’s degree in Data Science, Mathematics, Computer Science, or related field, or equivalent experience.
b. At least 5 years of industry experience in data science.
This position at Microsoft emphasizes the need for individuals with a strong understanding of Azure services and a passion for solving complex, real-world business problems using data science tools.
ProArch is a global technology consulting firm, and they are hiring for the position of data scientist. This role is focused on developing predictive models, analyzing complex datasets, and implementing machine learning concepts in production environments. ProArch is an excellent fit for professionals with experience in natural language processing (NLP), large language models (LLMs), and machine learning operations (MLOps).
Key Responsibilities:
a. Collaborate with stakeholders to identify key business metrics.
b. Perform exploratory data analysis (EDA) and data audits.
c. Implement machine learning algorithms and create dashboards using tools like PowerBI.
d. Deploy and maintain data management systems and back-end data infrastructure.
Qualifications:
a. Bachelor’s degree in Data Science, Data Analytics, or a related field. Advanced degrees (Master’s or Ph.D.) are preferred.
b. Proficiency in programming languages like Python, R, Java, or Kotlin.
c. Experience with big data analytics (Spark, Hadoop) and data visualization tools (PowerBI, Tableau).
This role requires a solid understanding of machine learning, data mining, and cloud-based infrastructure, making it ideal for candidates interested in building and deploying ML models at scale.
People Prime Worldwide is a global technology consulting and digital solutions company. The company is looking for a data scientist with expertise in statistics and Python but does not require machine learning or NLP knowledge. This role is heavily focused on statistical analysis, making it a great opportunity for professionals interested in the statistical aspects of data science.
Responsibilities:
a. Proficient use of Python and PySpark for statistics and statistical methods.
b. Perform regression, clustering, A/B testing, and hypothesis testing.
c. Work in PowerBI and update client dashboards as needed.
d. Collaborate with clients and communicate results effectively.
Qualifications:
a. A solid foundation in machine learning using Python.
b. 5 to 12 years of work experience in statistical analysis and data science.
The role stands out due to its emphasis on statistical methods over machine learning. The role is suitable for candidates who are more inclined toward statistics than AI/ML techniques.
EPAM Systems is known for its expertise in product development, digital platform engineering, and business consulting. The company is seeking a data scientist to design, develop, and implement novel machine-learning models to solve complex problems. This role is perfect for professionals who have a strong foundation in deep learning, computer vision, and distributed computing.
Key Responsibilities:
a. Design and implement machine learning models and algorithms.
b. Collaborate with data engineers and scientists to curate datasets for training.
c. Fine-tune and optimize models for performance, efficiency, and scalability.
d. Conduct experiments and evaluate the robustness of machine learning models using statistical methods.
Requirements:
a. Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
b. 3 to 5 years of experience in deep learning, computer vision, and NLP.
c. Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
The position at EPAM is ideal for data scientists who are interested in the technical side of model development, optimization, and evaluation. The role provides the opportunity to work with large-scale datasets and distributed computing frameworks, allowing for a deep dive into cutting-edge machine-learning techniques.
Accellor is hiring for the position of data scientist with a focus on predictive AI and Generative AI applications. This role involves overseeing the entire machine learning lifecycle, from data preparation to model deployment and management. It’s ideal for professionals with a hands-on approach to building machine learning models and experience in both predictive and generative AI.
Responsibilities:
a. Implement the full machine learning lifecycle, including data preparation, model building, deployment, and management.
b. Build predictive models and implement generative AI applications.
c. Collaborate with teams to ensure smooth data management and output consumption.
d. Maintain and deploy models within both predictive AI and Generative AI frameworks.
Requirements:
a. 3+ years of real-world business experience with data science projects.
b. Hands-on experience building and implementing machine learning models.
c. Proficiency in Python and experience with big data technologies like Spark.
d. Familiarity with tools like Streamlit for building applications and SQL for managing datasets.
Accellor’s position is perfect for data scientists with strong hands-on experience in machine learning and a solid understanding of big data technologies. The emphasis on generative AI sets this role apart, making it suitable for professionals looking to explore this growing field.
These positions encompass a variety of duties and necessary competencies, from crafting advanced machine learning algorithms to conducting statistical analysis and creating visual representations of data. Whether you're a seasoned professional in predictive AI or a devotee of statistical techniques, the present employment landscape is brimming with chances for development and progression in the domain of data science.