Lead Data Scientist – Machine Learning

3 weeks ago

Bengaluru, Karnataka, India Weekday (YC W21) Full time
Job Description

This role is for one of our clients

Industry: Technology, Information and Media

Seniority level: Mid-Senior level

Min Experience: 4 years

Location: Bengaluru

JobType: full-time

Were looking for an experienced Lead Data Scientist to join our dynamic and fast-growing data team. In this role, you&aposll lead impactful initiatives across the full machine learning lifecyclesolving real-world problems using data at scale. From ideation to deployment, youll bring clarity to business decisions through cutting-edge modeling and analytics.

If you&aposre passionate about applying machine learning to business challenges, mentoring others, and driving outcomes with data, we want you on our team.

What Youll Do

Lead end-to-end data science projects: Define problems, explore datasets, build predictive models, and deploy them into production systems.

Develop robust ML models using Python and its rich ecosystem (e.g., NumPy, Scikit-learn, Pandas, TensorFlow, PyTorch) tailored to real business use cases.

Collaborate cross-functionally with engineering, product, and business teams to align models with strategic goals and ensure seamless integration.

Conduct deep data exploration (EDA) to uncover trends, surface opportunities, and shape data-driven strategies.

Drive model performance monitoring, retraining pipelines, and A/B testing to ensure continuous improvement and stability post-deployment.

Mentor junior data scientists by reviewing code, guiding methodology, and promoting best practices in project execution.

Translate insights into action by presenting clear, concise results and recommendations to stakeholders and leadership.

Stay ahead of the curve by researching emerging tools, frameworks, and ML techniques to elevate team capabilities.

What You Bring

49 years of experience in data science, applied machine learning, and statistical modeling in a business or tech environment.

Strong command of Python and its ML ecosystem (Pandas, Scikit-learn, NumPy, Matplotlib, Seaborn).

Solid grasp of ML techniques supervised/unsupervised learning, regression/classification, ensemble methods, model validation, feature engineering.

Hands-on experience deploying models in production systems.

Proficient in working with large datasets, performing data cleaning, transformation, and ensuring data quality throughout the pipeline.

Excellent communication and stakeholder engagement skills you can clearly explain complex technical concepts to non-technical audiences.

Experience with version control systems (e.g., Git) and familiarity with cloud platforms (AWS, GCP, or Azure).

Strong analytical thinking and structured problem-solving ability.

Bonus Skills

Exposure to deep learning frameworks like TensorFlow or PyTorch.

Experience with distributed computing tools (e.g., Apache Spark, Dask).

Familiarity with ML Ops principles and production model monitoring.

Knowledge of data visualization and BI tools like Tableau, Power BI, or Looker.

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