Data Scientist

MhyMatch; New York (NY); Remote; USD 95,000 - 140,000; Full time

Benefits offered by this job

Competitive salary package with performance bonuses

Health insurance and retirement plans

Opportunities for continuous learning

Flexible working hours

Job summary

A leading product-based software company is looking for a skilled Data Scientist to leverage data for strategic decision-making. The role involves designing predictive models, collaborating with teams, and continuously improving data strategies. Ideal candidates will hold advanced degrees and have proficiency in relevant technologies including Python, R, and SQL, with a focus on data integrity and quality.

Qualifications

• Expert understanding of data science, machine learning, AI, and advanced analytics techniques.
• Advanced proficiency in statistical programming with Python and R.
• Strong experience with SQL and database management systems.

Responsibilities

• Design and implement statistical models and machine learning algorithms.
• Collaborate with cross-functional teams to provide data-driven solutions.
• Present findings to stakeholders and mentor junior team members.

Skills

Python

R

SQL

Data Visualization

Machine Learning

Analytical Thinking

Communication

Education

Masters degree or Ph.D. in Data Science, Computer Science, or Statistics

Tools

Tableau

Power BI

TensorFlow

PyTorch

Job description

Mode of Work: Remote

Brief Overview of the Job Description:

We are seeking a highly skilled Data Scientist to join our client, a leading product-based software company. This role leverages large volumes of data using modern tools and technologies to uncover insights, build predictive models, and contribute to strategic decision-making. It requires a blend of technical data science expertise, analytical problem-solving, and a passion for transforming data into actionable insights.

Key Responsibilities:

• Design and implement statistical models and machine learning algorithms to drive data-driven decision-making and support financial objectives.
• Optimize data strategies to reduce costs and improve data processing efficiency.
• Collaborate with cross-functional teams to understand business needs and provide data-driven solutions that enhance customer satisfaction.
• Present findings to stakeholders, translating complex data insights into understandable business decisions to meet customer expectations.
• Lead data mining and collection strategies to improve data reliability, efficiency, and quality across the organization.
• Develop and maintain robust data pipelines and ETL processes to ensure seamless data flow and integration.
• Continuously evaluate and identify new technologies, tools, and data sets to enhance the analytics capabilities of the organization.
• Implement and oversee data validation and cleansing processes to maintain data integrity and accuracy.
• Collaborate with IT and software development teams to integrate data solutions into existing systems and workflows.
• Stay updated with the latest industry trends and technologies to continually improve data science practices and methodologies.
• Participate in training and certification programs to enhance skills and knowledge in data science and analytics tools.
• Mentor and train junior team members to build a strong data science culture within the organization.
• Engage in continuous learning opportunities to stay ahead of technological advancements and best practices in data science.

Technologies to be Used:

• Python, R
• SQL and database management systems
• Data visualization tools such as Tableau or Power BI
• Machine learning frameworks like TensorFlow or PyTorch

Qualifications:

• Masters degree or Ph.D. in Data Science, Computer Science, Statistics, or a closely related field.
• Certifications in relevant technologies and frameworks are advantageous.

Knowledge:

• Expert understanding of data science, machine learning, AI, and advanced analytics techniques.

Skills:

• Advanced proficiency in Python and R for statistical programming and model development.
• Strong experience with SQL and database management systems.
• Skilled in data visualization tools such as Tableau or Power BI to convey insights visually.
• In-depth knowledge of machine learning frameworks like TensorFlow or PyTorch.
• Ability to work with both structured and unstructured data from various sources.
• Analytical and critical thinker with meticulous attention to detail.
• Ability to work in a dynamic environment and adapt to evolving business needs.
• Strong communication skills with the ability to explain complex solutions to non-technical stakeholders.
• Team player who is also capable of working independently.
• Dynamic and collaborative environment with a focus on innovation and continuous improvement.
• Supportive team culture that encourages knowledge sharing and professional growth.
• Flexible work arrangements to support work-life balance.

Key Performance Indicators:

• Accuracy and reliability of statistical models and predictive algorithms.
• Efficiency and effectiveness of data mining and collection strategies.
• Quality and clarity of data-driven insights presented to stakeholders.
• Adoption and impact of data-driven solutions on business processes and customer satisfaction.
• Continuous improvement in data science practices and methodologies.

Salary and Benefits:

• Competitive salary package with performance bonuses.
• Health insurance, retirement plans, and paid time off.
• Opportunities for continuous learning and professional development through workshops, courses, and conferences.
• Flexible working hours and potential for remote work arrangements.

Company Overview:

Our client is a leading product-based software company, dedicated to creating innovative and efficient solutions that address complex business challenges. Their suite of products enhances operational efficiencies and drives digital transformation, empowering businesses to achieve sustainable growth and competitive advantage.

Diversity Policy:

We are committed to creating a diverse environment and proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Clear pathways for career advancement in a supportive environment aimed at fostering professional growth and exploration of new technologies in the field of data science.