Description:

The Research Scientist (Data) position involves driving data-centric research projects and developing novel algorithms.
The role requires collaboration with a team of data scientists, engineers, and researchers to create pioneering data solutions and publish influential research.
Key responsibilities include conducting advanced data research and development, leading research on machine learning algorithms, statistical models, and data analysis techniques.
The scientist will develop and prototype new algorithms in areas such as predictive modeling, deep learning, NLP, and reinforcement learning.
Collaboration with cross-functional teams is essential to integrate research findings into scalable products.
The position also involves publishing research findings in top-tier journals and presenting at conferences to contribute to the scientific community.
Staying current with advancements in data science, machine learning, and AI is crucial, as is evaluating and implementing new technologies and tools.
The scientist will develop metrics for model validation and performance, ensuring models are rigorously tested and optimized.
Mentoring and guiding junior researchers is also a key responsibility, fostering a culture of continuous learning and experimentation.

Requirements:

Extensive experience in data science research with a strong understanding of statistical and machine learning algorithms, including supervised, unsupervised, and reinforcement learning methods is required.
Expertise in programming languages such as Python, R, or Julia, along with experience using libraries like TensorFlow, PyTorch, or Scikit-learn is necessary.
A strong foundation in mathematics, statistics, and data analysis techniques is essential, with comfort in complex data modeling and statistical inference.
Proven ability to design and implement advanced machine learning and AI algorithms, including deep learning, NLP, and time-series analysis is required.
Strong communication skills to convey complex ideas clearly and the ability to work collaboratively with both technical and non-technical teams are essential.
A Ph.D. or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field is required, with equivalent experience in advanced research considered.
A minimum of 5 years of experience in data research or a related field is required, with hands-on experience in designing and implementing models for large datasets.
Experience in publishing original research and presenting at industry or academic conferences is necessary, along with a background in developing data-driven solutions for real-world applications.

Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
Competitive vacation, sick leave, and 20 paid holidays per year are included in the benefits package.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs are available for professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources is offered.
Life insurance and short-term/long-term disability coverage are part of the benefits.
Confidential counseling and support services for personal and professional challenges are provided through an Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is available through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged.
Employee recognition programs are in place to celebrate achievements and milestones.