Senior Data Scientist - remote US
GridX, Inc. is seeking a talented and experienced Senior Data Scientist to join our team. Your responsibilities will include designing and constructing sophisticated machine learning models, running statistical analyses, as well as refining and updating existing systems.
We are looking for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
In order to thrive in this position, you must possess exceptional skills in statistics and machine learning, as well as a deep understanding of data science principles. Your ultimate objective will be to create highly efficient self-learning applications that can adapt and evolve over time.
- Design, train, and deploy machine learning algorithms in a scalable production setting
- Design and deploy data pipelines in a scalable production setting
- Collaborate with cross-functional teams, including engineering, product, and marketing, to design, develop, and track key performance indicators (KPIs) for models
- Conduct experiments to measure these KPIs, as well as deriving actionable insights from the data, to continually improve the technology and drive business outcomes
- Ensure data quality by implementing appropriate checks and cleaning
- Guide the data acquisition process
- Define and implement feature engineering
- Conduct statistical analysis to answer business questions, create dashboards, and present results to stakeholders
- A minimum of 5 years of hands-on experience as an individual contributor
- Demonstrated ability to write scalable production-quality code in Python, Java, Scala or a similar programming language, and to design and implement data engineering pipelines using technologies like Hive, SQL, BigQuery, Airflow, or Spark.
- Proficiency in machine learning frameworks and packages, such as Tensorflow, Pytorch, statsmodels, or scikit-learn
- Understanding of data structures and data modeling
- Deep knowledge of math, probability, statistics and algorithms
- Expertise in visualizing and manipulating big datasets
- Outstanding analytical and problem-solving skills
- Ability to work across time zones and with offshore teams in a dynamic start-up setting
- Demonstrable written, verbal, and visual communication skills
- Proficiency with the python data stack - Numpy, Scipy, pandas and similar
- Ability to select hardware to run an ML model with the required latency
- Experience mentoring and growing junior teammates
- Experience with software development practices including version control, continuous integration, and Agile methodologies
Compensation is determined by several factors which may include skillset, experience level, and geographic location. The expected base salary range for this role is $150,000 to $180,000 per year. Please note this range is an estimate and actual pay may vary based on qualifications and experience.
- Flexible PTO
- Excellent Medical, Dental and Vision Insurance
- 401k Match
- Stock Options
- Parental Leave
- Be part of creating our clean energy future
GridX is the catalyst of our clean energy future. Utilities and energy technology providers rely on our analytics solutions to tell people exactly what they can expect to pay when making clean energy decisions, like changing to a time-of-use rate plan, buying an electric vehicle, installing solar and more. The result is less strain on the electric grid, happier customers, and increased consumer investment in sustainable technologies. Working at GridX puts you at the center of realizing our clean energy future.
At GridX, we value the diversity of our employees and partners. We believe that our company thrives when we support and celebrate our differences.
No recruiters or phone calls, please. GridX does not accept unsolicited resumes from any agencies that have not signed a mutual service agreement. All unsolicited resumes and profiles will be considered GridX property, and GridX will not be obligated to pay a referral fee. This includes resumes submitted directly to hiring managers without contacting the Talent Acquisition Department.