Consultant / Sr. Consultant, Data Science
About Fresh Gravity:
Founded in 2015 and rapidly expanding, Fresh Gravity (www.freshgravity.com) is a business and technology consulting company at the cutting-edge of digital transformation. We drive digital success for our clients by helping them adopt transformative technologies that make them nimble, adaptive and responsive to their rapidly-changing business needs. Our unparalleled digital transformation expertise combines business strategy prowess with digital technologies know-how. Our expertise includes Data Management, Artificial Intelligence, Data Science & Analytics, and API Management & Integration.
In a short time, we have crafted an exceptional team who have delivered impactful projects for some of the largest corporations in the world. We are on a mission to solve the most complex business problems for our clients using the most exciting new technologies. And we are looking for top talent to join us in our quest.
Fresh Gravity’s team members are authorities in their field, but know how to have fun, too. We’re building an inspiring, open organization you’ll take pride in. We challenge ourselves to grow – every day. We create value for our clients and partners – every day. We promise rich opportunities for you to succeed, to shine, to exceed even your own expectations.
We are thoughtful. We are engaged. We are relentless. We are Fresh Gravity.
Fresh Gravity is an equal opportunity employer.
- Master’s degree in a quantitative discipline, e.g., Computer Science, Mathematics, Statistics, Artificial Intelligence.
- 3+ years of hands-on experience with statistical software tools. We prefer experience in Python and Python statistical libraries. Experience in R also accepted, as is SAS, SPSS, Strata, and Matlab.
- High proficiency with standard database skills (e.g., SQL), data preparation, cleaning, and wrangling/munging.
- Deep conceptual understanding of probability & statistics, ML algorithm intuition, and computer science fundamentals.
- Deep experience in statistical and machine learning techniques such as classification, regression, feature selection and feature engineering, hyperparameter tuning, unsupervised learning methods, etc.
- Experience with deep learning frameworks (e.g., TensorFlow, pyTorch, Caffe).
- Experience with noSQL databases (Cassandra, HBase, etc.)
- Experience with fundamental “building blocks” of AI, such as natural language processing and computer vision.
- Experience with less common techniques, such as probabilistic graphical models, generative algorithms, genetic algorithms, reinforcement learning, etc.
- Understanding of data visualization concepts and fundamentals, and/or experience with data visualization tools like Tableau.
- Personal projects and Kaggle competition results can serve as differentiation.
- Ability to explain statistical reasoning to both experts and non-experts
- Strong communication and interpersonal skills
- Ability to learn new skills/technologies quickly and independently
- Independent problem-solving skills
- Research machine learning algorithms, develop solution formulations, and test on large datasets.
- Given unstructured and complex business problems, design and develop tailored analytic solutions. Design experiments, test hypotheses, and build actionable models.
- Solve analytical problems, and effectively communicate methodologies and results.
- Draw relevant inferences and insights from data including identification of trends and anomalies.
- Translate unstructured, complex business problems into abstract mathematical frameworks, making intelligent analogies and approximations to produce working algorithms at scale.
About our Data Science and AI Capability teams:
- We are client- and peer- relationship focused. Our success comes from having happy clients and happy project teams.
- We are independent, but also thrive in a team environment. We aim for the best of both worlds: high autonomy plus high support and teamwork. Artificial Intelligence is an emerging field – we all learn from each other and each team member leads the way in some areas.
- Opportunities for “blue sky” and “art of the possible” thinking. We hire candidates both for what they know and for what they can imagine. We frequently work on emerging opportunities that don’t have a single “best practice” solution. If you come up with a great idea, you’ll get the green light to run with it!
- We learn from each other and share knowledge regularly: Because AI is an emerging area, we set aside time to stay up-to-date and share knowledge.