Join an Exciting Venture in Gurgaon: Senior Data Scientist

Company: Talent Nexa's Client, a B2B USA-based Product Company

Are you passionate about leveraging the power of alternative data to transform the world of investing? Do you thrive in a dynamic environment where innovation and data-driven decision-making are at the forefront? Join our San Francisco-based startup as a Senior Data Scientist and be part of a team driving impactful data-driven initiatives.

Position Overview:

As a Senior Data Scientist, you'll be instrumental in shaping our data-driven initiatives, utilizing advanced analytics to tackle complex challenges. Collaborating closely with cross-functional teams, you'll design and deploy machine learning models, analyze extensive datasets, and extract actionable insights to steer strategic decision-making.

Responsibilities:

- Lead the design, development, and implementation of advanced machine learning models to address complex business challenges.

- Analyze large datasets to uncover patterns, trends, and insights crucial for informed decision-making.

- Collaborate with stakeholders to define project requirements and develop scalable solutions meeting business objectives.

- Design and implement data pipelines and workflows to automate data collection, processing, and analysis tasks.

- Conduct exploratory data analysis, feature engineering, and model validation to ensure model accuracy and reliability.

- Stay updated with the latest advancements in data science, machine learning, and AI technologies, incorporating emerging tools and techniques.

- Communicate findings and recommendations effectively to technical and non-technical stakeholders.

- Mentor junior data scientists, fostering a culture of learning and best practices.

Requirements:

- Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, or related fields from a top-tier institution; Master's degree or MBA preferred.

- 4+ years of experience in data science or machine learning, with a minimum of 2 years hands-on experience.

- Proficiency in Python and SQL, with experience in object-oriented programming and production-level code development.

- Expertise in machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.

- Knowledge of statistics, machine learning algorithms, AI, and NLP techniques.

- Familiarity with version control systems (e.g., Git), CI tools, and cloud computing platforms (e.g., AWS).

- Experience with big data technologies like Apache Spark and building data pipelines.